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

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#!/usr/bin/env python3 import sys from os.path import abspath from os.path import dirname # 设置当前目录为工作目录 sys.path.insert(0, abspath(dirname(__file__))) # 引入 app.py import app # 必须有一个叫做 application 的变量 # gunicorn 就要这个变量 # 这个变量的值必须是 Flask 实例 # 这是规定的套路(协议) application = app.app # 这是把代码部署到 apache gunicorn nginx 后面的套路 """ ➜ ~ cat /etc/supervisor/conf.d/xx.conf [program:todo] command=/usr/local/bin/gunicorn wsgi --bind 0.0.0.0:2000 --pid /tmp/todo.pid directory=/root/web13 autostart=true """

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binhui.ni@yourdream.cc

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n=int(input()) li=list(map(int,input().split())) lis=list(map(int,input().split())) k=n-1 for i in range(n): if li[i]!=lis[k]: print("no") break k-=1 else: print("yes")

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@ignore_warnings(category=(DeprecationWarning, FutureWarning)) def check_regressors_train(name, regressor_orig): (X, y) = _boston_subset() y = StandardScaler().fit_transform(y.reshape((- 1), 1)) y = y.ravel() regressor = clone(regressor_orig) y = multioutput_estimator_convert_y_2d(regressor, y) rnd = np.random.RandomState(0) if ((not hasattr(regressor, 'alphas')) and hasattr(regressor, 'alpha')): regressor.alpha = 0.01 if (name == 'PassiveAggressiveRegressor'): regressor.C = 0.01 assert_raises(ValueError, regressor.fit, X, y[:(- 1)]) if (name in CROSS_DECOMPOSITION): y_ = np.vstack([y, ((2 * y) + rnd.randint(2, size=len(y)))]) y_ = y_.T else: y_ = y set_random_state(regressor) regressor.fit(X, y_) regressor.fit(X.tolist(), y_.tolist()) y_pred = regressor.predict(X) assert_equal(y_pred.shape, y_.shape) if (name not in ('PLSCanonical', 'CCA', 'RANSACRegressor')): assert_greater(regressor.score(X, y_), 0.5)

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#!/home/wizard/anaconda3/bin/python def main(): x = int(input('x=')) if x < 10: print('x={}'.format(x)) main()

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# coding: utf8 from __future__ import unicode_literals, print_function, division, absolute_import import importlib from zope.interface import Interface from pyramid.testing import Configurator from pyramid.httpexceptions import HTTPNotFound from purl import URL from clld.db.models.common import Contribution, ValueSet, Language, Language_files from clld.tests.util import TestWithEnv, Route, TESTS_DIR, WithDbAndDataMixin from clld.interfaces import IMapMarker from clld.web.adapters.download import N3Dump class Tests(WithDbAndDataMixin, TestWithEnv): def test_CLLDRequest(self): self.assertTrue(isinstance(self.env['request'].purl, URL)) c = self.env['request'].db.query(Contribution).first() self.env['request'].resource_url(c, ext='geojson') self.assertEqual(None, self.env['request'].ctx_for_url('/some/path/to/nowhere')) assert self.env['request'].ctx_for_url('/') self.env['request'].file_url(Language_files(id='1', object=Language.first())) assert self.env['request'].get_datatable('valuesets', ValueSet) assert self.env['request'].blog is None def test_menu_item(self): from clld.web.app import menu_item assert menu_item('contributions', None, self.env['request']) def test_ctx_factory(self): from clld.web.app import ctx_factory for model, route in [ (Contribution, 'contributions'), (ValueSet, 'valuesets'), (Language, 'languages'), ]: obj = model.first() self.set_request_properties( matchdict={'id': obj.id}, matched_route=Route(route)) ctx_factory(model, 'index', self.env['request']) ctx_factory(model, 'rsc', self.env['request']) self.set_request_properties(matchdict={'id': 'xxx'}) self.assertRaises( HTTPNotFound, ctx_factory, Contribution, 'rsc', self.env['request']) def test_MapMarker(self): marker = self.env['request'].registry.getUtility(IMapMarker) self.assertTrue(marker(None, self.env['request'])) def test_add_config_from_file(self): from clld.web.app import add_settings_from_file config = Configurator() add_settings_from_file(config, TESTS_DIR.joinpath('test.ini')) assert 'app:main.use' in config.registry.settings def test_config(self): class IF(Interface): pass config = Configurator( root_package=importlib.import_module('clld.web'), settings={ 'sqlalchemy.url': 'sqlite://', 'clld.pacific_centered_maps': True}) config.include('clld.web.app') # should have no effect, because a resource with this name is registered by # default: config.register_menu('languages', ('sources', dict(label='References'))) config.register_resource('language', None, None) config.register_resource('testresource', Language, IF, with_index=True, test=True) config.register_download(N3Dump(Language, 'clld')) config.add_301('/301pattern', 'http://example.org') config.add_410('/410pattern')

[ "xrotwang@googlemail.com" ]

xrotwang@googlemail.com

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/hemlock/database/types/__init__.py

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syfreed/hemlock_test2

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"""Custom Hemlock database types""" from hemlock.database.types.data_frame import DataFrame, DataFrameType from hemlock.database.types.function import Function, FunctionType from hemlock.database.types.markup import MarkupType

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/farmdation_project/farmdation/contrib/sites/migrations/0002_set_site_domain_and_name.py

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""" To understand why this file is here, please read: http://cookiecutter-django.readthedocs.org/en/latest/faq.html#why-is-there-a-django-contrib-sites-directory-in-cookiecutter-django """ # -*- coding: utf-8 -*- from __future__ import unicode_literals from django.conf import settings from django.db import migrations def update_site_forward(apps, schema_editor): """Set site domain and name.""" Site = apps.get_model("sites", "Site") Site.objects.update_or_create( id=settings.SITE_ID, defaults={ "domain": settings.WEBSITE_DOMAIN, "name": settings.WEBSITE_NAME } ) def update_site_backward(apps, schema_editor): """Revert site domain and name to default.""" Site = apps.get_model("sites", "Site") Site.objects.update_or_create( id=settings.SITE_ID, defaults={ "domain": "example.com", "name": "example.com" } ) class Migration(migrations.Migration): dependencies = [ ('sites', '0001_initial'), ] operations = [ migrations.RunPython(update_site_forward, update_site_backward), ]

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#!/usr/bin/env python # encoding: utf-8 """ @author: zhanghe @software: PyCharm @file: test_skf_categories.py @time: 2020-05-19 16:32 """ import csv import requests def test_get_skf_categories(csv_name, category_id): params = { 'id': category_id, 'language': 'en', 'source': 'webpim', 'site': '307', 'hits': 100, 'offset': 0, } url = 'https://search.skf.com/prod/search-skfcom/rest/apps/opc_v1/searchers/categories' header = ['Designation', 'd[mm]', 'D[mm]', 'B[mm]', 'C[kN]', 'Co[kN]', 'Pu[kN]', 'G-Speed[r/min]', 'O-Speed[r/min]'] out = open('skf_%s.csv' % csv_name, 'a') csv_write = csv.writer(out, dialect='excel') csv_write.writerow(header) c = 0 next_page = 0 while 1: if next_page == -1: break res = requests.get(url, params=params).json() rows = res.get('documentList', {}).get('documents', []) for r in rows: data = [r['title']] + r['table_values'] csv_write.writerow(data[:9]) c += 1 print(params['hits'] * next_page + len(rows)) if res.get('documentList', {}).get('numberOfHits', 0) > params['hits'] * next_page + len(rows): next_page += 1 else: next_page = -1 params['offset'] = params['hits'] * next_page out.close() print('共计%s行记录' % c) def run(): category_map = { 'angular_contact_ball_bearings': 'BA1_010', 'cylindrical_roller_bearings': 'BC1_010', 'angular_contact_thrust_ball_bearings_double_direction': 'BEA_010', 'angular_contact_thrust_ball_bearings_for_screw_drives_single direction': 'BDA_010', } for k, v in category_map.items(): test_get_skf_categories(k, v) if __name__ == '__main__': run()

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import socket import time import unittest2 as unittest from nose import SkipTest from kombu import BrokerConnection from kombu import Producer, Consumer, Exchange, Queue def consumeN(conn, consumer, n=1): messages = [] def callback(message_data, message): messages.append(message_data) message.ack() prev, consumer.callbacks = consumer.callbacks, [callback] while True: conn.drain_events(timeout=1) if len(messages) >= n: break consumer.callback = prev return messages class test_amqplib(unittest.TestCase): def purge(self, names): chan = self.connection.channel() map(chan.queue_purge, names) def setUp(self): self.connection = BrokerConnection(transport="amqplib") try: self.connection.connect() except socket.error: self.connected = False else: self.connected = True self.exchange = Exchange("tamqplib", "direct") self.queue = Queue("tamqplib", self.exchange, "tamqplib") def test_produce__consume(self): if not self.connected: raise SkipTest("Broker not running.") chan1 = self.connection.channel() producer = Producer(chan1, self.exchange) producer.publish({"foo": "bar"}, routing_key="tamqplib") chan1.close() chan2 = self.connection.channel() consumer = Consumer(chan2, self.queue) message = consumeN(self.connection, consumer) self.assertDictEqual(message[0], {"foo": "bar"}) chan2.close() self.purge(["tamqplib"]) def test_produce__consume_multiple(self): if not self.connected: raise SkipTest("Broker not running.") chan1 = self.connection.channel() producer = Producer(chan1, self.exchange) b1 = Queue("pyamqplib.b1", self.exchange, "b1") b2 = Queue("pyamqplib.b2", self.exchange, "b2") b3 = Queue("pyamqplib.b3", self.exchange, "b3") producer.publish("b1", routing_key="b1") producer.publish("b2", routing_key="b2") producer.publish("b3", routing_key="b3") chan1.close() chan2 = self.connection.channel() consumer = Consumer(chan2, [b1, b2, b3]) messages = consumeN(self.connection, consumer, 3) self.assertItemsEqual(messages, ["b1", "b2", "b3"]) chan2.close() self.purge(["pyamqplib.b1", "pyamqplib.b2", "pyamqplib.b3"]) def test_timeout(self): if not self.connected: raise SkipTest("Broker not running.") chan = self.connection.channel() self.purge([self.queue.name]) consumer = Consumer(chan, self.queue) self.assertRaises(socket.timeout, self.connection.drain_events, timeout=0.3) consumer.cancel() def test_basic_get(self): chan1 = self.connection.channel() producer = Producer(chan1, self.exchange) producer.publish({"basic.get": "this"}, routing_key="basic_get") chan1.close() chan2 = self.connection.channel() queue = Queue("amqplib_basic_get", self.exchange, "basic_get") queue = queue(chan2) queue.declare() for i in range(50): m = queue.get() if m: break time.sleep(0.1) self.assertEqual(m.payload, {"basic.get": "this"}) chan2.close() def tearDown(self): if self.connected: self.connection.close()

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from sklearn.feature_extraction import DictVectorizer from scipy import sparse def onehot_encode(tr,te,cols=None): if cols is None: cols = [i for i in tr.columns.values if i in te.columns.values] vec = DictVectorizer() for col in cols: tr[col] = tr[col].map(str) te[col] = te[col].map(str) print("start fitting") X = vec.fit_transform(tr[cols].T.to_dict().values()) Xt = vec.transform(te[cols].T.to_dict().values()) print("done fitting",X.shape,Xt.shape) return X,Xt def onehot_encode_bar(tr,te,cols=None,bar=10000): if cols is None: cols = [i for i in tr.columns.values if i in te.columns.values] vec = DictVectorizer() cat,num = [],[] for col in cols: nu = tr[col].unique().shape[0] if (nu<bar and nu>2) or tr[col].dtype=='object': cat.append(col) tr[col] = tr[col].map(str) te[col] = te[col].map(str) else: num.append(col) print("start fitting num of cat features:",len(cat)) X = vec.fit_transform(tr[cat].T.to_dict().values()) Xt = vec.transform(te[cat].T.to_dict().values()) print("done fitting",X.shape,Xt.shape) X = sparse.hstack([X,tr[num].values],format='csr') Xt = sparse.hstack([Xt,te[num].values],format='csr') return X,Xt

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aixueer4ever@gmail.com

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from output.models.nist_data.list_pkg.float_pkg.schema_instance.nistschema_sv_iv_list_float_min_length_2_xsd.nistschema_sv_iv_list_float_min_length_2 import NistschemaSvIvListFloatMinLength2 obj = NistschemaSvIvListFloatMinLength2( value=[ 4.9827486e+21, 3.5627644e+26, 5.6398728e+22, 8.9484692e+16, 5.2629679e+25, 6.6862685e+16, ] )

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# coding=utf-8 # Copyright 2021 The Google Research Authors. # # 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. """Utilities and common steps for model export.""" import os from typing import Any, Dict, List, Optional from absl import flags from absl import logging import numpy as np import tensorflow as tf from non_semantic_speech_benchmark.data_prep import data_prep_utils from non_semantic_speech_benchmark.distillation import frontend_lib from non_semantic_speech_benchmark.distillation import models from non_semantic_speech_benchmark.distillation.compression_lib import compression_op as compression from non_semantic_speech_benchmark.distillation.compression_lib import compression_wrapper def get_experiment_dirs(experiment_dir): """Returns a list of experiment directories. NOTE: This assumes that only folders with hyperparams in their name occur in the working dict. Args: experiment_dir: Base for all directories. Returns: List of specific experiment subdirs. """ if not tf.io.gfile.exists(experiment_dir): raise ValueError(f'Experiment dir doesn\'t exist: {experiment_dir}') experiment_dirs = [f for f in tf.io.gfile.listdir(experiment_dir) if tf.io.gfile.isdir(os.path.join(experiment_dir, f))] return experiment_dirs def get_params(experiment_dir_str): """Extracts hyperparams from experiment directory string. Args: experiment_dir_str: The folder-name for the set of hyperparams. Eg: '1-al=1.0,ap=False,lr=0.0001,ms=small,tbs=512' Returns: A dict mapping param key (str) to eval'ed value (float/eval/string). """ parsed_params = {} start_idx = experiment_dir_str.find('-') + 1 for kv in experiment_dir_str[start_idx:].split(','): cur_split = kv.split('=') if len(cur_split) != 2: raise ValueError(f'Folder doesn\'t split properly: {kv}') key, value = cur_split try: value = eval(value) # pylint: disable=eval-used except: # pylint: disable=bare-except pass parsed_params[key] = value return parsed_params def get_default_compressor(): compression_params = compression.CompressionOp.get_default_hparams().parse('') compressor = compression_wrapper.get_apply_compression( compression_params, global_step=0) return compressor def get_model(checkpoint_folder_path, params, tflite_friendly, checkpoint_number = None, include_frontend = False): """Given folder & training params, exports SavedModel without frontend.""" # Optionally override frontend flags from # `non_semantic_speech_benchmark/export_model/tf_frontend.py` override_flag_names = ['frame_hop', 'n_required', 'num_mel_bins', 'frame_width'] for flag_name in override_flag_names: if flag_name in params: setattr(flags.FLAGS, flag_name, params[flag_name]) static_model = models.get_keras_model( params['mt'], bottleneck_dimension=None, output_dimension=1024, truncate_output=params['tr'] if 'tr' in params else False, frontend=include_frontend, compressor=None, tflite=tflite_friendly) checkpoint = tf.train.Checkpoint(model=static_model) if checkpoint_number: checkpoint_to_load = os.path.join( checkpoint_folder_path, f'ckpt-{checkpoint_number}') assert tf.train.load_checkpoint(checkpoint_to_load) else: checkpoint_to_load = tf.train.latest_checkpoint(checkpoint_folder_path) checkpoint.restore(checkpoint_to_load).expect_partial() return static_model def convert_tflite_model(model, quantize, model_path): """Uses TFLiteConverter to convert a Keras Model. Args: model: Keras model obtained from get_tflite_friendly_model. quantize: Whether to quantize TFLite model using dynamic quantization. See: https://www.tensorflow.org/lite/performance/post_training_quant model_path: Path for TFLite file. """ converter = tf.lite.TFLiteConverter.from_keras_model(model) converter.target_spec.supported_ops = [ tf.lite.OpsSet.TFLITE_BUILTINS, # enable TensorFlow Lite ops. # There is a GatherV2 op in the frontend that isn't supported by TFLite # as a builtin op. (It works as a TFLite builtin only if the sample size # to the frontend is a constant) # However, TFLite supports importing some relevant operators from TF, # at the cost of binary size (~ a few MB). # See: https://www.tensorflow.org/lite/guide/ops_select # NOTE: This has no effect on the model/binary size if the graph does not # required the extra TF ops (for example, for no-frontend versio tf.lite.OpsSet.SELECT_TF_OPS # enable TensorFlow ops. ] if quantize: converter.optimizations = [tf.lite.Optimize.DEFAULT] tflite_buffer = converter.convert() with tf.io.gfile.GFile(model_path, 'wb') as f: f.write(tflite_buffer) logging.info('Exported TFLite model to %s.', model_path) def sanity_check( include_frontend, model_path, embedding_dim, tflite, n_required = None, frame_width = None, num_mel_bins = None): """Sanity check model by running dummy inference.""" n_required = n_required or flags.FLAGS.n_required frame_width = frame_width or flags.FLAGS.frame_width num_mel_bins = num_mel_bins or flags.FLAGS.num_mel_bins if include_frontend: input_shape = (1, 2 * n_required) expected_output_shape = (7, embedding_dim) else: feats_inner_dim = frontend_lib.get_frontend_output_shape()[0] * frame_width input_shape = (1, feats_inner_dim, num_mel_bins, 1) expected_output_shape = (1, embedding_dim) logging.info('Input shape: %s. Expected output shape: %s', input_shape, expected_output_shape) model_input = np.zeros(input_shape, dtype=np.float32) if tflite: logging.info('Building tflite interpreter...') interpreter = data_prep_utils.build_tflite_interpreter( model_path) logging.info('Running inference...') output = data_prep_utils.samples_to_embedding_tflite( model_input, sample_rate=16000, interpreter=interpreter, output_key='0', name='sanity_check') else: logging.info('Loading and running inference with SavedModel...') model = tf.saved_model.load(model_path) output = model(model_input)['embedding'].numpy() np.testing.assert_array_equal(output.shape, expected_output_shape) logging.info('Model "%s" worked.', model_path)

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copybara-worker@google.com

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Ark-kun/tfx

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2021-07-25T05:58:15.168607

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# Lint as: python2, python3 # Copyright 2019 Google LLC. 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. """TFX Transform component definition.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from typing import Optional, Text, Union import absl from tfx import types from tfx.components.base import base_component from tfx.components.base import executor_spec from tfx.components.transform import executor from tfx.orchestration import data_types from tfx.types import artifact from tfx.types import artifact_utils from tfx.types import standard_artifacts from tfx.types.standard_component_specs import TransformSpec class Transform(base_component.BaseComponent): """A TFX component to transform the input examples. The Transform component wraps TensorFlow Transform (tf.Transform) to preprocess data in a TFX pipeline. This component will load the preprocessing_fn from input module file, preprocess both 'train' and 'eval' splits of input examples, generate the `tf.Transform` output, and save both transform function and transformed examples to orchestrator desired locations. ## Providing a preprocessing function The TFX executor will use the estimator provided in the `module_file` file to train the model. The Transform executor will look specifically for the `preprocessing_fn()` function within that file. An example of `preprocessing_fn()` can be found in the [user-supplied code]((https://github.com/tensorflow/tfx/blob/master/tfx/examples/chicago_taxi_pipeline/taxi_utils.py)) of the TFX Chicago Taxi pipeline example. ## Example ``` # Performs transformations and feature engineering in training and serving. transform = Transform( examples=example_gen.outputs['examples'], schema=infer_schema.outputs['schema'], module_file=module_file) ``` Please see https://www.tensorflow.org/tfx/transform for more details. """ SPEC_CLASS = TransformSpec EXECUTOR_SPEC = executor_spec.ExecutorClassSpec(executor.Executor) def __init__( self, examples: types.Channel = None, schema: types.Channel = None, module_file: Optional[Union[Text, data_types.RuntimeParameter]] = None, preprocessing_fn: Optional[Union[Text, data_types.RuntimeParameter]] = None, transform_graph: Optional[types.Channel] = None, transformed_examples: Optional[types.Channel] = None, input_data: Optional[types.Channel] = None, instance_name: Optional[Text] = None, enable_cache: Optional[bool] = None): """Construct a Transform component. Args: examples: A Channel of type `standard_artifacts.Examples` (required). This should contain the two splits 'train' and 'eval'. schema: A Channel of type `standard_artifacts.Schema`. This should contain a single schema artifact. module_file: The file path to a python module file, from which the 'preprocessing_fn' function will be loaded. The function must have the following signature. def preprocessing_fn(inputs: Dict[Text, Any]) -> Dict[Text, Any]: ... where the values of input and returned Dict are either tf.Tensor or tf.SparseTensor. Exactly one of 'module_file' or 'preprocessing_fn' must be supplied. preprocessing_fn: The path to python function that implements a 'preprocessing_fn'. See 'module_file' for expected signature of the function. Exactly one of 'module_file' or 'preprocessing_fn' must be supplied. transform_graph: Optional output 'TransformPath' channel for output of 'tf.Transform', which includes an exported Tensorflow graph suitable for both training and serving; transformed_examples: Optional output 'ExamplesPath' channel for materialized transformed examples, which includes both 'train' and 'eval' splits. input_data: Backwards compatibility alias for the 'examples' argument. instance_name: Optional unique instance name. Necessary iff multiple transform components are declared in the same pipeline. enable_cache: Optional boolean to indicate if cache is enabled for the Transform component. If not specified, defaults to the value specified for pipeline's enable_cache parameter. Raises: ValueError: When both or neither of 'module_file' and 'preprocessing_fn' is supplied. """ if input_data: absl.logging.warning( 'The "input_data" argument to the Transform component has ' 'been renamed to "examples" and is deprecated. Please update your ' 'usage as support for this argument will be removed soon.') examples = input_data if bool(module_file) == bool(preprocessing_fn): raise ValueError( "Exactly one of 'module_file' or 'preprocessing_fn' must be supplied." ) transform_graph = transform_graph or types.Channel( type=standard_artifacts.TransformGraph, artifacts=[standard_artifacts.TransformGraph()]) if not transformed_examples: example_artifact = standard_artifacts.Examples() example_artifact.split_names = artifact_utils.encode_split_names( artifact.DEFAULT_EXAMPLE_SPLITS) transformed_examples = types.Channel( type=standard_artifacts.Examples, artifacts=[example_artifact]) spec = TransformSpec( examples=examples, schema=schema, module_file=module_file, preprocessing_fn=preprocessing_fn, transform_graph=transform_graph, transformed_examples=transformed_examples) super(Transform, self).__init__( spec=spec, instance_name=instance_name, enable_cache=enable_cache)

[ "tensorflow-extended-team@google.com" ]

tensorflow-extended-team@google.com

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/tours/migrations/0039_auto_20190923_2153.py

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lalit1796/mytrip

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# Generated by Django 2.2.2 on 2019-09-23 16:23 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('tours', '0038_auto_20190923_2151'), ] operations = [ migrations.AlterField( model_name='package', name='uid', field=models.CharField(default='--uid--', max_length=200, unique=True), ), ]

[ "lalitsingh1796@gmail.com" ]

lalitsingh1796@gmail.com

d41f85e2c73f965a8555cd3f6da0967a0e321fde

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/videos/api/serializers.py

462b50c2b48ff27afdefbc67ced6a79e795bd6b4

[]

no_license

pedrofolch/digitalsoil

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refs/heads/master

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from rest_framework import serializers from videos.models import Video class VideoSerializer(serializers.ModelSerializer): uri = serializers.SerializerMethodField(read_only=True) class Meta: model = Video fields = [ 'uri', 'pk', 'title', 'embed_code', 'share_message', 'order', 'tags', 'slug', 'active', 'featured', 'free_preview', 'category', 'timestamp', 'updated' ] read_only_fields = ['user', 'order', ] def get_uri(self, obj): request = self.context.get('request') return obj.get_api_url(request=request) def validate_title(self, value): """We want the title to be unique""" qs = Video.objects.filter(title__iexact=value) # including instance if self.instance: qs = qs.exclude(pk=self.instance.pk) if qs.exists(): raise serializers.ValidationError("This title has already been used") return value

[ "pedro.folch@gmail.com" ]

pedro.folch@gmail.com

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74a30d76f49051ec0200a847fe83431a9501f3d7

/address_func.py

a5b6612a9078be5ba1d28b66d635386fd78f59b7

[]

no_license

Milziade/nano_dash

97e827ac24c5e8f3d97e8de69e151afd4d7d8fac

00618fa1f6d425b63f6ada625569eadda69a0176

refs/heads/master

2023-05-01T02:36:51.595622

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import requests import pandas as pd import random import colors def get_json(nano_address): action = { 'action': 'account_history', 'account': nano_address, 'count': '-1' } r = requests.post('https://mynano.ninja/api/node', json=action).json() if 'error' in r: return False return r['history'] def get_df(history): df = pd.DataFrame().from_dict(history) df = df.replace('nano_3kwppxjcggzs65fjh771ch6dbuic3xthsn5wsg6i5537jacw7m493ra8574x', 'FreeNanoFaucet.com') df = df.replace('nano_34prihdxwz3u4ps8qjnn14p7ujyewkoxkwyxm3u665it8rg5rdqw84qrypzk', 'nano-faucet.org') df = df.replace('nano_3pg8khw8gs94c1qeq9741n99ubrut8sj3n9kpntim1rm35h4wdzirofazmwt', 'nano.trade') df = df.replace('nano_1tyd79peyzk4bs5ok1enb633dqsrxou91k7y4zzo1oegw4s75bokmj1pey4s', 'Apollo Faucet') df['amount'] = [int(i)/10**30 for i in df['amount']] df['local_timestamp'] = pd.to_datetime(df['local_timestamp'], unit='s') del df['hash'] del df['height'] return df.to_dict('records'), df.columns.values def get_balance(nano_address): action = { "action": "account_info", "account": nano_address } r = requests.post('https://mynano.ninja/api/node', json=action).json() return int(r['balance'])/10**30 def pie_chart(df): receive_acc = list(set(item['account'] for item in df if item['type'] == 'receive')) amount_receive = {i: 0 for i in receive_acc} send_acc = list(set(item['account'] for item in df if item['type'] == 'send')) amount_send = {i: 0 for i in send_acc} for d in df: key = d['account'] if key in amount_receive: amount_receive[key] += d['amount'] else: amount_send[key] += d['amount'] return list(amount_receive.keys()), list(amount_receive.values()), \ list(amount_send.keys()), list(amount_send.values()) def balance_over_time(df: dict): # Otteniamo il momento, il tipo di transazione e l'ammontare time = list([item['type'], item['amount'], str(item['local_timestamp']).split()[0]] for item in df) # Se l'account invia soldi, l'ammontare per il bilancio diviene negativo for item in time: if item[0] == 'send': item[1] = -item[1] time_n = [time[i][2] for i in range(len(time))] # Date e orari di ogni transazione insta_bal = [time[i][1] for i in range(len(time))] overall_bal = [0] # Bilancio cumulativo for i in range(len(time)): x = time[-1-i][1] + overall_bal[-1] overall_bal.append(x) overall_bal.pop(0) return overall_bal, list(reversed(time_n)), list(reversed(insta_bal)) def get_colors(n): # creates n different color colors_list = [] for i in range(n): cols = colors.colors col = random.choice(cols) #cols.remove(col) colors_list.append(col) return colors_list

[ "you@example.com" ]

you@example.com

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/deployment-scripts/scripts/infrastructure/openstack/openstack-create-instance.py

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[]

no_license

marjancek/Showcase

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refs/heads/master

2021-01-15T09:08:48.146581

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from novaclient.v1_1 import client as novaclient from common.Cloudscale import * from scripts.common.Cloudscale import check_args, parse_args class CreateInstance: def __init__(self, cfg): self.cfg = cfg self.user = cfg.get('OPENSTACK', 'username') self.pwd = cfg.get('OPENSTACK', 'password') self.url = cfg.get('OPENSTACK', 'auth_url') self.tenant = cfg.get('OPENSTACK', 'tenant_name') self.image_name = cfg.get('OPENSTACK', 'image_name') server = self.create_instance() print [s['addr'] for s in server.addresses[self.tenant] if s['OS-EXT-IPS:type'] == 'floating'][0] def create_instance(self): nc = novaclient.Client(self.user, self.pwd, self.tenant, auth_url=self.url) for f in nc.flavors.list(): print f for server in nc.servers.list(): if server._info['name'] == self.instance_name: return server if __name__ == '__main__': check_args(1, "<config_path>") _, cfg, _, _ = parse_args() CreateInstance(cfg)

[ "simon.ivansek@xlab.si" ]

simon.ivansek@xlab.si

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/04-day/main.py

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[ "MIT" ]

permissive

timbook/advent-of-code-2020

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refs/heads/main

2023-01-25T01:19:02.520349

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import re from functools import reduce raw = open('input.txt', 'r').read().split('\n\n') class Passport: required_fields = ['byr', 'iyr', 'eyr', 'hgt', 'hcl', 'ecl', 'pid'] def __init__(self, entry): fields = re.split('\s', entry.strip()) self.fields = {field.split(':')[0]:field.split(':')[1] for field in fields} def is_valid_a(self): return all(req in self.fields for req in self.required_fields) def is_valid_b(self): return self.is_valid_a() and reduce( lambda a, b: a and b, [ self.is_valid_byr(), self.is_valid_iyr(), self.is_valid_eyr(), self.is_valid_hgt(), self.is_valid_hcl(), self.is_valid_ecl(), self.is_valid_pid() ] ) def is_valid_byr(self): byr = self.fields['byr'] return re.match('\d{4}', byr) and (1920 <= int(byr) <= 2002) def is_valid_iyr(self): iyr = self.fields['iyr'] return re.match('\d{4}', iyr) and (2010 <= int(iyr) <= 2020) def is_valid_eyr(self): eyr = self.fields['eyr'] return re.match('\d{4}', eyr) and (2020 <= int(eyr) <= 2030) def is_valid_hgt(self): hgt = self.fields['hgt'][:-2] unit = self.fields['hgt'][-2:] if unit == 'cm': return re.match('\d+', hgt) and (150 <= int(hgt) <= 193) elif unit == 'in': return re.match('\d+', hgt) and (59 <= int(hgt) <= 76) else: return False def is_valid_hcl(self): hcl = self.fields['hcl'] return bool(re.match('#[0-9a-f]{6}', hcl)) def is_valid_ecl(self): return self.fields['ecl'] in ['amb', 'blu', 'brn', 'gry', 'grn', 'hzl', 'oth'] def is_valid_pid(self): return bool(re.match('^\d{9}$', self.fields['pid'])) passports = [Passport(line) for line in raw] n_valid = sum(ppt.is_valid_a() for ppt in passports) print(f"A :: Number of valid passports: {n_valid}") # 199 too high n_valid = sum(ppt.is_valid_b() for ppt in passports) print(f"B :: Number of valid passports: {n_valid}")

[ "timothykbook@gmail.com" ]

timothykbook@gmail.com

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d16c15f2fb433c6b5874ea49ff5db89315e9711d

/benchmarks/comparison-with-addict.py

2f6c181632636f0ac48d33a840027e004ad8d8d9

[ "MIT" ]

permissive

vltr/middle

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refs/heads/develop

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import cProfile import sys from enum import Enum from enum import IntEnum from enum import unique from typing import Dict from typing import List from typing import Set # --------------------------------------------------------------- # # Import boilerplate # --------------------------------------------------------------- # try: import timy import middle from addict import Dict as ADict except ImportError: print( "To run this script, you must install these dependencies:", file=sys.stderr, ) print("- addict", file=sys.stderr) print("- middle", file=sys.stderr) print("- timy", file=sys.stderr) sys.exit(1) # --------------------------------------------------------------- # # Fixed variables # --------------------------------------------------------------- # TOTAL_LOOPS = 1_000_000 if "short" in sys.argv: TOTAL_LOOPS = 1 # --------------------------------------------------------------- # # Enum definition # --------------------------------------------------------------- # @unique class PlatformEnum(str, Enum): XBOX1 = "XBOX1" PLAYSTATION4 = "PLAYSTATION4" PC = "PC" @unique class LanguageEnum(IntEnum): ENGLISH = 1 JAPANESE = 2 SPANISH = 3 GERMAN = 4 PORTUGUESE = 5 @unique class CityRegionEnum(str, Enum): TROPICAL = "TROPICAL" TEMPERATE = "TEMPERATE" BOREAL = "BOREAL" # --------------------------------------------------------------- # # middle model definition # --------------------------------------------------------------- # class MiddleCity(middle.Model): name: str = middle.field() region: CityRegionEnum = middle.field() class MiddleGame(middle.Model): name: str = middle.field() platform: PlatformEnum = middle.field() score: float = middle.field() resolution_tested: str = middle.field() genre: List[str] = middle.field() rating: Dict[str, float] = middle.field() players: Set[str] = middle.field() language: LanguageEnum = middle.field() awesome_city: MiddleCity = middle.field() # --------------------------------------------------------------- # # Test variable # --------------------------------------------------------------- # MODEL_INSTANCE = { "name": "Cities: Skylines", "platform": "PC", "score": 9.0, "resolution_tested": "1920x1080", "genre": ["Simulators", "City Building"], "rating": {"IGN": 8.5, "Gamespot": 8.0, "Steam": 4.5}, "players": ["Flux", "strictoaster"], "language": 1, "awesome_city": {"name": "Blumenau", "region": "TEMPERATE"}, } # --------------------------------------------------------------- # # Test runnable # --------------------------------------------------------------- # def test_addict(): game = ADict(MODEL_INSTANCE) assert isinstance(game.name, str) assert isinstance(game.platform, str) assert isinstance(game.score, float) assert isinstance(game.resolution_tested, str) assert isinstance(game.genre, list) assert isinstance(game.rating, dict) assert isinstance(game.players, list) assert isinstance(game.language, int) assert isinstance(game.awesome_city, dict) assert isinstance(game.awesome_city.name, str) assert isinstance(game.awesome_city.region, str) def test_middle(): game = MiddleGame(**MODEL_INSTANCE) assert isinstance(game, MiddleGame) assert isinstance(game.name, str) assert isinstance(game.platform, PlatformEnum) assert isinstance(game.score, float) assert isinstance(game.resolution_tested, str) assert isinstance(game.genre, list) assert isinstance(game.rating, dict) assert isinstance(game.players, set) assert isinstance(game.language, LanguageEnum) assert isinstance(game.awesome_city, MiddleCity) assert isinstance(game.awesome_city.name, str) assert isinstance(game.awesome_city.region, CityRegionEnum) # --------------------------------------------------------------- # # Run tests # --------------------------------------------------------------- # def main(): if "profile" in sys.argv: cProfile.run( "for i in range({}): test_addict()".format(TOTAL_LOOPS), sort="tottime", ) cProfile.run( "for i in range({}): test_middle()".format(TOTAL_LOOPS), sort="tottime", ) else: timy.timer(ident="addict", loops=TOTAL_LOOPS)(test_addict).__call__() timy.timer(ident="middle", loops=TOTAL_LOOPS)(test_middle).__call__() if __name__ == "__main__": main()

[ "rkuesters@gmail.com" ]

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def main(): n,k=[int(i) for i in input().split(' ')] a=[1]*(n+1) for i in range(1,min(k, n+1)): a[i]=a[i-1]+a[i-1] if k <= n: a[k]=sum([a[j] for j in range(k)]) for i in range(k+1, n+1): a[i]=a[i-1]+a[i-1]-a[i-k-1] print(str(a[n])) main()

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class Car: def __init__(self, name: str, model: str, engine: str): self.name = name self.model = model self.engine = engine def get_info(self): return f'This is {self.name} {self.model} with engine {self.engine}' car = Car("Kia", "Rio", "1.3L B3 I4") print(car.get_info())

[ "dim.damianov@gmail.com" ]

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/user_portrait/cron/flow4/zmq_work_weibo_flow4.py

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[]

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yuwendong/user_portrait

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# -*- coding=utf-8 -*- import re import sys import zmq import time import json import math from datetime import datetime reload(sys) sys.path.append('../../') from time_utils import ts2datetime, datetime2ts from global_utils import R_CLUSTER_FLOW2 as r_cluster from global_config import ZMQ_VENT_PORT_FLOW4, ZMQ_CTRL_VENT_PORT_FLOW4,\ ZMQ_VENT_HOST_FLOW1, ZMQ_CTRL_HOST_FLOW1 from global_config import SENSITIVE_WORDS_PATH f = open(SENSITIVE_WORDS_PATH, 'rb') # test #f = open('/home/ubuntu8/huxiaoqian/user_portrait/user_portrait/cron/flow2/zz.txt', 'rb') def load_sensitive_words(): ZZ_WORD = [] for line in f: line_list = line.split('=') word = line_list[0] ZZ_WORD.append(word.decode('utf-8')) f.close() return ZZ_WORD SENSITIVE_WORD = load_sensitive_words() print 'sensitive_word:', SENSITIVE_WORD def cal_text_work(item): uid = item['uid'] timestamp = item['timestamp'] date = ts2datetime(timestamp) ts = datetime2ts(date) #print 'ts:', date, ts text = item['text'] if isinstance(text, str): text = text.decode('utf-8', 'ignore') RE = re.compile(u'#([a-zA-Z-_⺀-⺙⺛-⻳⼀-⿕々〇〡-〩〸-〺〻㐀-䶵一-鿃豈-鶴侮-頻並-龎]+)#', re.UNICODE) hashtag_list = RE.findall(text) if hashtag_list: # there all use unicode· hashtag_dict = dict() for hashtag in hashtag_list: try: hashtag_dict[hashtag] += 1 except: hashtag_dict[hashtag] = 1 try: hashtag_count_string = r_cluster.hget('hashtag_'+str(ts), str(uid)) #print 'key:hashtag_'+ str(ts) #print 'hget hashtag result:', hashtag_count_string hashtag_count_dict = json.loads(hashtag_count_string) for hashtag in hashtag_dict: count = hashtag_dict[hashtag] try: hashtag_count_dict[hashtag] += count except: hashtag_count_dict[hashtag] = count #print 'hashtag_count_dict:', hashtag_count_dict r_cluster.hset('hashtag_'+str(ts), str(uid), json.dumps(hashtag_count_dict)) except: #print 'hash_dict:', hashtag_dict r_cluster.hset('hashtag_'+str(ts), str(uid), json.dumps(hashtag_dict)) def cal_text_sensitive(item): text = item['text'] uid = item['uid'] timestamp = item['timestamp'] date = ts2datetime(timestamp) ts = datetime2ts(date) if isinstance(text, str): text = text.decode('utf-8', 'ignore') sensitive_result = [word for word in SENSITIVE_WORD if word in text] if sensitive_result: sensitive_dict = dict() for word in sensitive_result: try: sensitive_dict[word] += 1 except: sensitive_dict[word] = 1 #print 'sensitive_dict:', sensitive_dict try: sensitive_count_string = r_cluster.hget('sensitive_'+str(ts), str(uid)) #print 'key:sensitive_', str(ts) #print 'hget sensitive result:', sensitive_count_string sensitive_count_dict = json.loads(sensitive_count_string) for word in sensitive_dict: count = sensitive_dict[word] try: sensitive_count_dict[word] += count except: sensitive_count_dict[word] = count #print 'sensitive_count_dict:', sensitive_count_dict r_cluster.hset('sensitive_'+str(ts), str(uid), json.dumps(sensitive_count_dict)) except: #print 'sensitive:', sensitive_dict r_cluster.hset('sensitive_'+str(ts), str(uid), json.dumps(sensitive_dict)) if __name__ == "__main__": """ receive weibo """ context = zmq.Context() receiver = context.socket(zmq.PULL) receiver.connect('tcp://%s:%s' %(ZMQ_VENT_HOST_FLOW1, ZMQ_VENT_PORT_FLOW4)) controller = context.socket(zmq.SUB) controller.connect("tcp://%s:%s" %(ZMQ_VENT_HOST_FLOW1, ZMQ_CTRL_VENT_PORT_FLOW4) count = 0 tb = time.time() ts = tb while 1: try: item = receiver.recv_json() except Exception, e: print Exception, ":", e if not item: continue if item['sp_type'] == '1': try: if item and (item['message_type']==1 or item['message_type']==3): cal_text_work(item) cal_text_sensitive(item) except: pass count += 1 if count % 10000 == 0: te = time.time() print '[%s] cal speed: %s sec/per %s' % (datetime.now().strftime('%Y-%m-%d %H:%M:%S'), te - ts, 10000) #if count % 100000 == 0: # print '[%s] total cal %s, cost %s sec [avg %s per/sec]' % (datetime.now().strftime('%Y-%m-%d %H:%M:%S'), count, te - tb, count / (te - tb)) ts = te

[ "1257819385@qq.com" ]

1257819385@qq.com

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# arc086_a.py import collections N, K = map(int, input().split()) A = list(map(int, input().split())) C = collections.Counter(A) C = sorted(C.values()) lenght = len(C) # print(lenght, K, C) print(sum(C[:(lenght-K)]))

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katuhito/workspace13

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# 3目並べ import random goal = [ 0b111000000, 0b000111000, 0b000000111, 0b100100100, 0b010010010, 0b001001001, 0b100010001, 0b001010100 ] # 3つ並んだか判定 def check(player): for mask in goal: if player & mask == mask: return True return False # 交互に置く def play(p1, p2): if check(p2): #3つ並んだら出力して終了 print([bin(p1), bin(p2)]) return board = p1 | p2 if board == 0b111111111: #すべて置いたら引き分けで終了 print([bin(p1), bin(p2)]) return # 置ける場所を探す w = [i for i in range(9) if(board & (1 << i)) == 0] # ランダムに置いてみる r = random.choice(w) play(p2, p1 | (1 << r)) #手番を入れ替えて次を探す play(0, 0)

[ "katuhitohara@gmail.com" ]

katuhitohara@gmail.com

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import matplotlib.pyplot as plt def grid_axes_labels(axes, xlabel=None, ylabel=None, **kws): plt.setp(axes.flat, xlabel="", ylabel="") if xlabel is not None: for ax in axes[-1]: ax.set_xlabel(xlabel, **kws) if ylabel is not None: for ax in axes[:, 0]: ax.set_ylabel(ylabel, **kws)

[ "mwaskom@stanford.edu" ]

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/04_factory/pizza_store/lib/pizza.py

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# coding: utf-8 from abc import ABC, abstractmethod class Pizza(ABC): def __init__(self, ingredient_factory): """ :param lib.pizza_factory.PizzaIngredientFactory ingredient_factory: """ self._ingredient_factory = ingredient_factory self._name = None self._dough = None self._sauce = None self._veggies = [] self._cheese = None self._pepperoni = None self._clam = None @abstractmethod def prepare(self): pass def bake(self): print('350度で25分間焼く') def cut(self): print('ピザを扇型に切り分ける') def box(self): print('PizzaStoreの正式な箱にピザを入れる') def set_name(self, name): self._name = name def get_name(self): return self._name class CheesePizza(Pizza): def prepare(self): print('{}を下処理'.format(self._name)) self._dough = self._ingredient_factory.create_dough() self._sauce = self._ingredient_factory.create_sauce() self._cheese = self._ingredient_factory.create_cheese() class ClamPizza(Pizza): def prepare(self): print('{}を下処理'.format(self._name)) self._dough = self._ingredient_factory.create_dough() self._sauce = self._ingredient_factory.create_sauce() self._cheese = self._ingredient_factory.create_cheese() self._clam = self._ingredient_factory.create_clam()

[ "denzow@gmail.com" ]

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import os, sys, util sys.path.append(os.getcwd()) from src.assistant.exec.commandList import CommandList from src.assistant.exec.parser import VoiceCommandParser command_list = CommandList("EN-US") parser = VoiceCommandParser(command_list) def test_parse_system_command(): command_instance = parser.parse("repeat hello world") target_command = command_list.get_command_instance_by_voice_command("repeat") assert command_instance.system_command.lower() == "repeat" assert command_instance.args.lower() == "hello world" assert command_instance.info == target_command.info def test_parse_user_command(): voice_command, terminal_command = util.generate_random_user_command() command_list.set_user_command(voice_command, {"terminal_command": terminal_command}) other_voice_command = voice_command + " and something more" other_terminal_command = terminal_command + " and something more" command_list.set_user_command(other_voice_command, {"terminal_command": other_terminal_command}) argument1, argument2 = "a docile dog eating meet", "a cute cat sleeping" command_instance = parser.parse(voice_command + " " + argument1) other_command_instance = parser.parse(other_voice_command + " " + argument2) assert command_instance.terminal_command == terminal_command assert command_instance.args.lower() == argument1 assert other_command_instance.terminal_command == other_terminal_command assert other_command_instance.args.lower() == argument2

[ "jeangamerextreme@gmail.com" ]

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import os, sys, re, math N,K = list(map(int,input().split(' '))) A = list(map(int,input().split(' '))) d = math.ceil(math.log2(1e+12)) ones = [0 for _ in range(d)] for a in A: s = bin(a)[::-1] for i in range(len(s)-2): if s[i] == '1': ones[i] += 1 X = 0 for di in range(d-1,-1,-1): if X + 2 ** di <= K and ones[di] <= N * 0.5: X += 2 ** di ret = 0 for a in A: ret += X ^ a print(ret)

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from d2l import AllDeepLearning as d2l from mxnet import autograd, gluon, init, nd from mxnet.gluon import nn import numpy as np """ Mini batches w←w−η_t*g_t where gt=∂_wf(x_t,w) We can increase the computational efficiency of this operation by applying it to a minibatch of observations at a time. That is, we replace the gradient gt over a single observation by one over a small batch gt= 1/|B_t| * ∂w∑i∈B_t(f(xi,w)) """ def get_data_ch11(batch_size=10, n=1500): data = np.genfromtxt("E:\\Python_Data\\airfoil_self_noise.dat", dtype=np.float32) data = (data - data.mean(axis=0)) / data.std(axis=0) data_iter = d2l.load_array((data[:n, :-1], data[:n, -1]), batch_size, is_train=True) return data_iter, data.shape[1] - 1 def sgd(params, states, hyper_params): for p in params: p[:] -= hyper_params['lr'] * p.grad def train_ch11(trainer_fn, state, hyper_params, data_iter, feature_dim, num_epochs=2): w = nd.random.normal(scale=0.01, shape=(feature_dim, 1)) b = nd.zeros(1) w.attach_grad() b.attach_grad() net, loss = lambda X: d2l.linreg(X, w, b), d2l.squared_loss animator = d2l.Animator(xlabel='epoch', ylabel='loss', xlim=[0, num_epochs], ylim=[0.22, 0.32]) n, timer = 0, d2l.Timer() for _ in range(num_epochs): for X, y in data_iter: with autograd.record(): l = loss(net(X), y).mean() l.backward() trainer_fn([w, b], state, hyper_params) n += X.shape[0] if n % 200 == 0: timer.stop() animator.add(n / X.shape[0] / len(data_iter), d2l.evaluate_loss(net, data_iter, loss)) timer.start() print('loss: %.3f, %.3f sec/epoch' % (animator.Y[0][-1], timer.avg())) return timer.cumsum(), animator.Y[0] def train_sgd(lr, batch_size, num_epochs=2): data_iter, feature_dim = get_data_ch11(batch_size) return train_ch11(sgd, None, {'lr': lr}, data_iter, feature_dim, num_epochs) gd_res = train_sgd(1, 1500, 10) sgd_res = train_sgd(0.005, 1) mini1_res = train_sgd(.4, 100) mini2_res = train_sgd(.05, 10) d2l.set_figsize([6, 3]) d2l.plot(*list(map(list, zip(gd_res, sgd_res, mini1_res, mini2_res))), 'time (sec)', 'loss', xlim=[1e-2, 10], legend=['gd', 'sgd', 'batch size = 100', 'batch size = 10']) d2l.plt.gca().set_xscale('log') d2l.plt.show() def train_gluon_ch11(tr_name, hyper_params, data_iter, num_epochs=2): net = nn.Sequential() net.add(nn.Dense(1)) net.initialize(init.Normal(sigma=.01)) trainer = gluon.Trainer(net.collect_params(), tr_name, hyper_params) loss = gluon.loss.L2Loss() animator = d2l.Animator(xlabel='epoch', ylabel='loss', xlim=[0, num_epochs], ylim=[0.22, 0.35]) n, timer = 0, d2l.Timer() for _ in range(num_epochs): for X, y in data_iter: with autograd.record(): l = loss(net(X), y) l.backward() trainer.step(X.shape[0]) n += X.shape[0] if n % 200 == 0: timer.stop() animator.add(n / X.shape[0]/len(data_iter), (d2l.evaluate_loss(net, data_iter, loss))) timer.start() print('loss: %.3f, %.3f sec/epoch' % (animator.Y[0][-1], timer.avg())) data_iter, _ = get_data_ch11(10) train_gluon_ch11('sgd', {'learning_rate': 0.05}, data_iter) d2l.plt.show() """ Vectorization makes code more efficient due to reduced overhead arising from the deep learning framework and due to better memory locality and caching on CPUs and GPUs. There is a trade-off between statistical efficiency arising from SGD and computational efficiency arising from processing large batches of data at a time. Minibatch stochastic gradient descent offers the best of both worlds: computational and statistical efficiency. In minibatch SGD we process batches of data obtained by a random permutation of the training data (i.e., each observation is processed only once per epoch, albeit in random order). It is advisable to decay the learning rates during training. In general, minibatch SGD is faster than SGD and gradient descent for convergence to a smaller risk, when measured in terms of clock time. """

[ "bluexker@gmail.com" ]

bluexker@gmail.com

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def change (aint,alst): aint = 0 alst[0] = 0 alst.append(4) print('aint:',aint) print('alst:',alst) aint = 3 alst = [1,2,3] print('1',aint) print('1',alst) change(aint,alst) print('3',aint) print('3',alst)

[ "285957109@qq.com" ]

285957109@qq.com

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/subset/comp_rank_grlex.py

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[]

no_license

pdhhiep/Computation_using_Python

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407ed29fddc267950e9860b8bbd1e038f0387c97

refs/heads/master

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#!/usr/bin/env python def comp_rank_grlex ( kc, xc ): #*****************************************************************************80 # ## COMP_RANK_GRLEX computes the graded lexicographic rank of a composition. # # Discussion: # # The graded lexicographic ordering is used, over all KC-compositions # for NC = 0, 1, 2, ... # # For example, if KC = 3, the ranking begins: # # Rank Sum 1 2 3 # ---- --- -- -- -- # 1 0 0 0 0 # # 2 1 0 0 1 # 3 1 0 1 0 # 4 1 1 0 1 # # 5 2 0 0 2 # 6 2 0 1 1 # 7 2 0 2 0 # 8 2 1 0 1 # 9 2 1 1 0 # 10 2 2 0 0 # # 11 3 0 0 3 # 12 3 0 1 2 # 13 3 0 2 1 # 14 3 0 3 0 # 15 3 1 0 2 # 16 3 1 1 1 # 17 3 1 2 0 # 18 3 2 0 1 # 19 3 2 1 0 # 20 3 3 0 0 # # 21 4 0 0 4 # .. .. .. .. .. # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 30 October 2014 # # Author: # # John Burkardt # # Parameters: # # Input, int KC, the number of parts in the composition. # 1 <= KC. # # Input, int XC[KC], the composition. # For each 1 <= I <= KC, we have 0 <= XC(I). # # Output, int RANK, the rank of the composition. # from i4_choose import i4_choose from i4vec_sum import i4vec_sum from sys import exit import numpy as np # # Ensure that 1 <= KC. # if ( kc < 1 ): print ''; print 'COMP_RANK_GRLEX - Fatal error!' print ' KC < 1' exit ( 'COMP_RANK_GRLEX - Fatal error!' ) # # Ensure that 0 <= XC(I). # for i in range ( 0, kc ): if ( xc[i] < 0 ): print '' print 'COMP_RANK_GRLEX - Fatal error!' print ' XC[I] < 0' exit ( 'COMP_RANK_GRLEX - Fatal error!' ); # # NC = sum ( XC ) # nc = i4vec_sum ( kc, xc ) # # Convert to KSUBSET format. # ns = nc + kc - 1 ks = kc - 1 xs = np.zeros ( ks, dtype = np.int32 ) xs[0] = xc[0] + 1 for i in range ( 2, kc ): xs[i-1] = xs[i-2] + xc[i-1] + 1 # # Compute the rank. # rank = 1; for i in range ( 1, ks + 1 ): if ( i == 1 ): tim1 = 0 else: tim1 = xs[i-2]; if ( tim1 + 1 <= xs[i-1] - 1 ): for j in range ( tim1 + 1, xs[i-1] ): rank = rank + i4_choose ( ns - j, ks - i ) for n in range ( 0, nc ): rank = rank + i4_choose ( n + kc - 1, n ) return rank def comp_rank_grlex_test ( ): #*****************************************************************************80 # ## COMP_RANK_GRLEX_TEST tests COMP_RANK_GRLEX. # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 30 October 2014 # # Author: # # John Burkardt # from comp_random_grlex import comp_random_grlex print '' print 'COMP_RANK_GRLEX_TEST' print ' A COMP is a composition of an integer N into K parts.' print ' Each part is nonnegative. The order matters.' print ' COMP_RANK_GRLEX determines the rank of a COMP' print ' from its parts.' print '' print ' Actual Inferred' print ' Test Rank Rank' print '' kc = 3 rank1 = 20 rank2 = 60 seed = 123456789 for test in range ( 0, 5 ): xc, rank3, seed = comp_random_grlex ( kc, rank1, rank2, seed ) rank4 = comp_rank_grlex ( kc, xc ) print ' %4d %6d %8d' % ( test, rank3, rank4 ) # # Terminate. # print '' print 'COMP_RANK_GRLEX_TEST:' print ' Normal end of execution.' return if ( __name__ == '__main__' ): from timestamp import timestamp timestamp ( ) comp_rank_grlex_test ( ) timestamp ( )

[ "siplukabir@gmail.com" ]

siplukabir@gmail.com

917f1e4058d8ddec0274a5dd448fc901123da679

e1f53cb481f2b6ea2ac3ee53d0251c5d9ea782e0

/src/pyaid/xml/XMLConfigParser.py

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[]

no_license

hannahp/PyAid

8771ee35c2fdf9503e68e808dc0028e885e68158

b9562a954552334fab16c32a6b8285ea3e1571e0

refs/heads/master

2021-01-22T14:02:26.068735

2014-01-29T23:33:33

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# XMLConfigParser.py # (C)2011 # Scott Ernst import re import xml.dom.minidom as minidom import codecs from pyaid.xml.ConfigData import ConfigData #___________________________________________________________________________________________________ XMLConfigParser class XMLConfigParser(object): """XMLConfigParser.""" #=================================================================================================== # C L A S S TYPE_ID = 'xml' #=================================================================================================== # P U B L I C #___________________________________________________________________________________________________ parseFile @staticmethod def parseFile(path, target=None, parseToInterchangeFormat =False): fh = codecs.open(path, 'r', 'utf-8') xml = fh.read() fh.close() return XMLConfigParser.parse(xml, target, parseToInterchangeFormat) #___________________________________________________________________________________________________ parse @staticmethod def parse(xml, target=None, parseToInterchangeFormat =False): # Removes whitespace between tags to reduce potential parsing issues. pattern = re.compile('\<\?xml(.*)\?\>') if pattern.search(xml) is None: xml = '<?xml version="1.0" encoding="utf-8"?>' + xml dom = minidom.parseString(re.sub('>[\n\r\s\t]+<','><',xml)) if target is None: target = {} cd = ConfigData() for node in dom.childNodes[0].childNodes: # Ignore whitespace generated text nodes if isinstance(node, (minidom.Comment, minidom.Text)): continue XMLConfigParser._parseNode(node, cd) if parseToInterchangeFormat: cd.writeToInterchangeDict(target) else: cd.writeToDict(target) return target #___________________________________________________________________________________________________ serializeToFile @staticmethod def serializeToFile(targetFile, interchangeData): xml = XMLConfigParser.serializeToXML(interchangeData) fh = codecs.open(targetFile, 'wb', 'utf-8') fh.write(xml) fh.close() #___________________________________________________________________________________________________ serialize @staticmethod def serialize(interchangeData): xml = '<vm>\n' for n,v in interchangeData.iteritems(): xml += XMLConfigParser._writeNode(n, v) return (xml + '</vm>').decode('unicode_escape') #=================================================================================================== # P R I V A T E #___________________________________________________________________________________________________ _writeNode @staticmethod def _writeNode(name, data, depth =1): indent = (' '*4*depth) target = indent + '<' if isinstance(data, list): d = '|'.join(data[1]) if isinstance(data[1], list) else str(data) target += data[0] + ' n="' + name + '" v="' + d + '" />\n' elif isinstance(data, dict): target += 'o n="' + name + '">\n' for n,v in data.iteritems(): target += XMLConfigParser._writeNode(n, v, depth+1) target += indent + '</o>' elif isinstance(data, str): target += 's' + 'n="' + name + '" v="' + data + '" />\n' elif isinstance(data, (int, float)): target += 'n' + 'n="' + name + '" v="' + str(data) + '" />\n' else: target += 'unknown n="' + name + '" />' return target #___________________________________________________________________________________________________ _parseNode @staticmethod def _parseNode(node, configData): nodeName = node.getAttribute('n') nodeType = node.tagName if nodeType != 'o': XMLConfigParser._parseAttribute(nodeName, nodeType, node.getAttribute('v'), configData) return cd = ConfigData() for k in node.attributes.keys(): if k != 'n': aValue = node.getAttribute(k) aType = 's' if aValue.find(':') != -1: aValue = node.getAttribute(k).split(':') aType = str(aValue[0]) aValue = aValue[-1] XMLConfigParser._parseAttribute(k, aType, aValue, cd) for child in node.childNodes: XMLConfigParser._parseNode(child, cd) configData.setItem(nodeName, 'o', cd) #___________________________________________________________________________________________________ _parseAttribute @staticmethod def _parseAttribute(attrName, attrType, attrValue, configData): configData.setItem(attrName, attrType, attrValue)

[ "swernst@gmail.com" ]

swernst@gmail.com

8c0a4f5b85c510d63ce5695baafd7aac77604f94

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/compare_SV_groups_to_trees.py

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[]

no_license

standardgalactic/kuhner-python

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30b73554cc8bc9d532c8108b34dd1a056596fec7

refs/heads/master

2023-07-07T04:18:30.634268

2020-04-06T04:37:48

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# -*- coding: utf-8 -*- """ Created on Thu Oct 4 12:43:41 2018 @author: Lucian """ from __future__ import division from os import walk from os import path from os import readlink from os import mkdir from os.path import isfile from copy import deepcopy import numpy import math import matplotlib.pyplot as plt import csv import ete3 #import lucianSNPLibrary as lsl groupdir = "SNV_groups/" treedir = "phylip_TS_analysis/" SVfile = "SV_events.txt" patientfile = "patient_analysis_SVs.tsv" allg_outfile = "all_groups_SVs.tsv" #outdir = "SNV_SV_tree_compare" + tag + "/" #if not path.isdir(outdir): # mkdir(outdir) groupfiles = [] for __, _, files in walk(groupdir): groupfiles += files def callGroup(group, allsamples, tree): if len(group) == 1: return "Singleton" if len(group) == len(allsamples): return "Root" trueset = set() falseset = set() for branch in tree: if branch.name != "": for sample in group: if sample in branch.name: trueset.add(branch) for sample in allsamples: if sample in group: continue if sample in branch.name: falseset.add(branch) if "blood" in branch.name: tree.set_outgroup(branch) trueroot = tree.get_common_ancestor(trueset) for fbranch in falseset: testset = trueset.copy() testset.add(fbranch) newroot = tree.get_common_ancestor(testset) if newroot == trueroot: return "Ungrouped" return "Grouped" # Read in the SNV numbers groupdata = {} allsamples= {} for gfile in groupfiles: if "all" in gfile or "patient" in gfile or "SV_" in gfile: continue patient = gfile.split("_")[0] groupdata[patient] = {} allsamples[patient] = set() for line in open(groupdir + gfile, "r"): if "Patient" in line: continue lvec = line.rstrip().split() assert(patient == lvec[0]) count = int(lvec[1]) perc = float(lvec[2]) samples = tuple(lvec[3:]) groupdata[patient][samples] = {} groupdata[patient][samples]["count"] = count groupdata[patient][samples]["percentage"] = perc groupdata[patient][samples]["SV_count"] = 0 for sample in samples: allsamples[patient].add(sample) #Read in the SV numbes SVs = {} samplelists = {} for line in open(SVfile, "r"): if "chr" in line: continue lvec = line.rstrip().split() (__, __, patient, sample, type, ch1, start1, end1, __, ch2, start2, end2, __, __, __, __) = lvec svid = (type, ch1, start1, end1, ch2, start2, end2) if patient not in SVs: SVs[patient] = {} if svid not in SVs[patient]: SVs[patient][svid] = set() SVs[patient][svid].add(sample) #Count the SVs by sample list nmulti = 0 nmulti_singletons = 0 nmulti_multis = 0 nsingle = 0 SVcounts = {} for patient in SVs: SVtotal = 0 for segid in SVs[patient]: samples = list(SVs[patient][segid]) samples.sort() samples = tuple(samples) if samples not in groupdata[patient]: groupdata[patient][samples] = {} groupdata[patient][samples]["count"] = 0 groupdata[patient][samples]["percentage"] = 0.0 groupdata[patient][samples]["SV_count"] = 0 groupdata[patient][samples]["SV_count"] += 1 SVtotal += 1 nsingle += 1 for samples in groupdata[patient]: groupdata[patient][samples]["SV_percentage"] = groupdata[patient][samples]["SV_count"]/SVtotal print("Number of segments with a single call:", str(nsingle)) print("Number of segments with multiple calls:", str(nmulti)) print("Number of segments with multiple calls, all singletons:", str(nmulti_singletons)) print("Number of segments with multiple calls, all multiples:", str(nmulti_multis)) #Now put the tree data in there, too: for patient in groupdata: treefilename = treedir + patient + "_outtree.txt" if patient == "891": treefilename = treedir + patient + "a_outtree.txt" tree = ete3.Tree(treefilename) for samples in groupdata[patient]: groupdata[patient][samples]["matches_tree"] = callGroup(samples, allsamples[patient], tree) #And finally, write out all of our information. outfile = open(groupdir + allg_outfile, "w") outfile.write("Patient\tMatches_tree\tCount\tPercentage\tSV count\tSV percentage\tSample1\tSample2\tSample3\tSample4\tSample5\tSample6\n") for patient in groupdata: for samples in groupdata[patient]: outfile.write(patient) outfile.write("\t" + groupdata[patient][samples]["matches_tree"]) outfile.write("\t" + str(groupdata[patient][samples]["count"])) outfile.write("\t" + str(groupdata[patient][samples]["percentage"])) outfile.write("\t" + str(groupdata[patient][samples]["SV_count"])) outfile.write("\t" + str(groupdata[patient][samples]["SV_percentage"])) for sample in samples: outfile.write("\t" + sample) outfile.write("\n") outfile.close() #Now do some analysis has23GD = ["74", "279", "303", "391", "396", "450", "772", "997"] types = ["Singleton", "Root", "Grouped", "Ungrouped"] outfile = open(groupdir + patientfile, "w") outfile.write("Patient\tnSNVmin\tnSNVmax\thas 2-3 GD") for type in types: outfile.write("\t" + type + " counts") outfile.write("\t" + type + " total") outfile.write("\tUngrouped potential subclone counts\tUngrouped potential scomubclone total\n") for patient in groupdata: smallestSNVcount = 100000 maxSNVcount = 0 for samples in groupdata[patient]: SNVcount = groupdata[patient][samples]["count"] if groupdata[patient][samples]["matches_tree"] == "Grouped": if SNVcount < smallestSNVcount: smallestSNVcount = SNVcount if SNVcount > maxSNVcount: maxSNVcount = SNVcount possibleSubcloneThreshold = smallestSNVcount*3/4 SVcounts = {} for match in types: SVcounts[match] = [] SVcounts["subclones"] = [] for samples in groupdata[patient]: theseSamples = groupdata[patient][samples] SVcount = theseSamples["SV_count"] if SVcount ==0: continue if theseSamples["matches_tree"] == "Ungrouped" and theseSamples["count"] >= possibleSubcloneThreshold: SVcounts["subclones"].append(SVcount) else: SVcounts[theseSamples["matches_tree"]].append(SVcount) outfile.write(patient) outfile.write("\t" + str(possibleSubcloneThreshold)) outfile.write("\t" + str(maxSNVcount)) outfile.write("\t" + str(patient in has23GD)) for type in types: outfile.write("\t") for num in SVcounts[type]: outfile.write("//" + str(num)) outfile.write("\t" + str(sum(SVcounts[type]))) outfile.write("\t") for num in SVcounts["subclones"]: outfile.write("//" + str(num)) outfile.write("\t" + str(sum(SVcounts["subclones"]))) outfile.write("\n") outfile.close()

[ "lpsmith@uw.edu" ]

lpsmith@uw.edu

5a2a55a993186bacf8fed7bada23f6ab0264b6b5

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/pippy/fx/experimental/refinement_types.py

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permissive

yunxing/tau

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2022-09-30T23:13:56

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# Copyright (c) Meta Platforms, Inc. and affiliates class Equality: def __init__(self, lhs, rhs): self.lhs = lhs self.rhs = rhs def __str__(self): return f'{self.lhs} = {self.rhs}' def __repr__(self): return f'{self.lhs} = {self.rhs}' def __eq__(self, other): if isinstance(other, Equality): return self.lhs == other.lhs and self.rhs == other.rhs else: return False

[ "noreply@github.com" ]

yunxing.noreply@github.com

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/psgreet.py

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no_license

ravijaya/sep28

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refs/heads/master

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name = input('enter the name :') city = input('enter the city :') zip_code = int(input('enter the postal code :')) print('name :', name) print('city :', city) print(zip_code) print(type(zip_code))

[ "ravi.goglobium@gmail.com" ]

ravi.goglobium@gmail.com

e095bb08830df4cb39df6e6f8c0f7a370cf6d071

524baf7de05bd3fc5b9d08083cbb0b7b47a67979

/40.py

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gk90731/100-questions-practice

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refs/heads/master

2020-05-25T14:04:59.642819

2019-05-21T12:49:04

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'''Question: Please try to guess what is missing in the following code and add the missing part so that the code works fine. import math print(math.pow(2))''' import math print(math.pow(2,3))

[ "gk90731@gmail.com" ]

gk90731@gmail.com

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/99_backup/25_各国历年二氧化碳CO2排放量统计分析/challenge7_1.py

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echo-xr/pc

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refs/heads/master

2020-04-26T16:54:03.408688

2019-03-03T11:27:34

null

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null

UTF-8

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def co2(): import pandas as pd # 读取 Data 表 data = pd.read_excel('ClimateChange.xlsx') # 取 'Series code' 这列中值为 'EN.ATM.CO2E.KT' 的行并设置索引 data = data[data['Series code']=='EN.ATM.CO2E.KT'].set_index('Country code') # 刪掉多余的前五列，只留各年排量数据 data.drop(data.columns[:5], axis=1, inplace=True) # 把数组中值为 '..' 的元素替换成 'NaN' data.replace({'..': pd.np.nan}, inplace=True) # 对 NaN 空值进行向前和向后填充 data = data.fillna(method='ffill', axis=1).fillna(method='bfill', axis=1) # 读取 Country 表 country = pd.read_excel('ClimateChange.xlsx', 'Country') # 设置国家代号为索引，方便合并数据 country.index = country['Country code'] # 合并这俩 Series ：国家总排量和国家收入属于什么群体 df = pd.concat([data.sum(axis=1), country['Income group']], axis=1) # Sum emissions a = df.groupby('Income group').sum() # 设置列名 a.columns = ['Sum emissions'] # 在 df 中加入一列国家名字 df[2] = country['Country name'] # 各收入群体中排放量最高的国家和最高排放量 h = df.sort_values(0, ascending=False).groupby('Income group').head(1).set_index('Income group') # 设置列名 h.columns = ['Highest emissions', 'Highest emission country'] # 各收入群体中排放量最低的国家和最低排放量 l = df[df[0]>0].sort_values(0).groupby('Income group').head(1).set_index('Income group') # 设置列名 l.columns = ['Lowest emissions', 'Lowest emission country'] # 返回全部数据, concat 会自动对 index 排序 return pd.concat([a, h, l], axis=1)

[ "1195581533@qq.com" ]

1195581533@qq.com

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/moodledata/vpl_data/125/usersdata/172/29042/submittedfiles/ap1.py

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rafaelperazzo/programacao-web

95643423a35c44613b0f64bed05bd34780fe2436

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refs/heads/master

2021-01-12T14:06:25.773146

2017-12-22T16:05:45

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# -*- coding: utf-8 -*- a=float(input('digite o 1° número:')) b=float(input('digite o 2° número:')) c=float(input('digite o 3° número:')) if a<=b and a<=c: print(a) if b<=c: print(b) print(c) else : print(c) print(b)

[ "rafael.mota@ufca.edu.br" ]

rafael.mota@ufca.edu.br

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/tests/unit/services/storage/test_base.py

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[ "MIT" ]

permissive

totem/cluster-deployer

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refs/heads/develop

2022-10-12T09:09:30.417412

2017-06-30T22:32:56

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2014-09-08T04:03:06

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import datetime from freezegun import freeze_time from mock import MagicMock from nose.tools import raises import pytz from deployer.services.storage.base import AbstractStore from tests.helper import dict_compare NOW = datetime.datetime(2022, 01, 01, tzinfo=pytz.UTC) NOW_NOTZ = datetime.datetime(2022, 01, 01) class TestAbstractStore: def setup(self): self.store = AbstractStore() @raises(NotImplementedError) def test_get(self): self.store.create_deployment(MagicMock()) @raises(NotImplementedError) def test_get_deployment(self): self.store.get_deployment('fake_id') @raises(NotImplementedError) def test_update_state(self): self.store.update_state('fake_id', 'PROMOTED') @raises(NotImplementedError) def test_update_runtime_upstreams(self): self.store.update_runtime_upstreams('fake_id', {}) @raises(NotImplementedError) def test_update_runtime_units(self): self.store.update_runtime_units('fake_id', []) @raises(NotImplementedError) def test_update_state_bulk(self): self.store.update_state_bulk('myapp', 'DECOMMISSIONED') @raises(NotImplementedError) def test_get_health(self): self.store.health() @freeze_time(NOW_NOTZ) def test_add_event(self): # Given: Mock implementation for adding raw event self.store._add_raw_event = MagicMock() # When: I add event to the store self.store.add_event('MOCK_EVENT') # Then: Event gets added to the store self.store._add_raw_event.assert_called_once_with({ 'type': 'MOCK_EVENT', 'component': 'deployer', 'details': None, 'date': NOW_NOTZ }) @raises(NotImplementedError) def test_add_raw_event(self): self.store.add_event({}) def test_setup(self): self.store.setup() # NOOP @raises(NotImplementedError) def test_find_apps(self): self.store.find_apps() @raises(NotImplementedError) def test_filter_deployments(self): self.store.filter_deployments('myapp') @freeze_time(NOW) def test_apply_modified_ts(self): # When: I apply modified timestamp for given deployemnt deployement = self.store.apply_modified_ts({ 'deployement': { 'id': 'test' } }) # Then: Modified timestamp is applied as expected dict_compare(deployement, { 'deployement': { 'id': 'test' }, 'modified': NOW })

[ "sukrit007@gmail.com" ]

sukrit007@gmail.com

d4e55b4a3c1058d466250a81fc43250a26f6e81e

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/PythonGTK/Examples/19_cellRendererPixbuf.py

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[]

no_license

ashutoshm1771/Source-Code-from-Tutorials

d5f950db8f5f648e87303835e9558eeba404939a

f5552d4bd0f4bebcf5c674ff730fcb61f2d7a1ce

refs/heads/master

2020-09-15T06:08:31.777622

2019-11-22T09:08:31

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2019-11-22T09:01:51

2019-11-22T09:01:48

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from gi.repository import Gtk class CellRendererPixbufWindow(Gtk.Window): def __init__(self): Gtk.Window.__init__(self, title="CellRendererPixbuf Example") self.set_default_size(200, 200) self.liststore = Gtk.ListStore(str, str) self.liststore.append(["New", "document-new"]) self.liststore.append(["Open", "document-open"]) self.liststore.append(["Save", "document-save"]) treeview = Gtk.TreeView(model=self.liststore) renderer_text = Gtk.CellRendererText() column_text = Gtk.TreeViewColumn("Text", renderer_text, text=0) treeview.append_column(column_text) renderer_pixbuf = Gtk.CellRendererPixbuf() column_pixbuf = Gtk.TreeViewColumn("Image", renderer_pixbuf, icon_name=1) treeview.append_column(column_pixbuf) self.add(treeview) win = CellRendererPixbufWindow() win.connect("delete-event", Gtk.main_quit) win.show_all() Gtk.main()

[ "buckyroberts@gmail.com" ]

buckyroberts@gmail.com

f7fb4d9a7d5027b2266d958ce939e45c3c255fd8

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/past202010/h/main.py

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[]

no_license

ryu19-1/atcoder_python

57de9e1db8ff13a107b5861f8f6a231e40366313

cc24b3c2895aad71d40cefbb8e2893dc397b8f4f

refs/heads/master

2023-05-10T05:32:16.507207

2021-05-19T17:48:10

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#!/usr/bin/env python3 import sys from collections import deque, Counter from heapq import heappop, heappush from bisect import bisect_right from itertools import accumulate sys.setrecursionlimit(10**6) INF = 10**12 m = 10**9 + 7 def main(): N, M, K = map(int, input().split()) S = [list(input()) for _ in range(N)] # countを二次元累積和でもっておく count = [[[0] * (M+1) for _ in range(N+1)] for _ in range(10)] for i in range(N): for j in range(M): count[int(S[i][j])][i+1][j+1] += 1 for k in range(10): for i in range(N): for j in range(M): count[k][i + 1][j + 1] += count[k][i + 1][j] for j in range(M+1): count[k][i + 1][j] += count[k][i][j] # print(count[1]) for n in range(min(N, M), 0, -1): # print(n) for i in range(N - n + 1): for j in range(M - n + 1): # (i,j)~(i+n,j+n)の中にある数字の数+Kがn**2を超えていたらok for k in range(10): # print(n, i, j, k) cnt = count[k][i + n][j + n] - count[k][i + n][j] - count[k][i][j + n] + count[k][i][j] if cnt + K >= n * n: print(n) exit() if __name__ == "__main__": main()

[ "ryu1007kami@gmail.com" ]

ryu1007kami@gmail.com

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/Щелчок/15_поляков/22.py

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no_license

Pochemu/Activity

8e2a7ec4f6b7fd233c0ee48e893733b077aac7a4

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refs/heads/main

2023-07-09T04:04:06.337321

2021-07-06T21:38:26

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for i in range(101, 1000): x = i L = x - 21 M = x + 12 while L != M: if L > M: L = L - M else: M = M - L if M == 11: print(i)

[ "48361330+Pochemu@users.noreply.github.com" ]

48361330+Pochemu@users.noreply.github.com

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/Python/Programmers/Level3/리틀프렌즈사천성.py

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no_license

louisuss/Algorithms-Code-Upload

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6c97c713858b075162d5d86f124c0555f383c5b0

refs/heads/master

2023-01-08T21:37:19.702276

2020-11-09T04:03:50

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def find_route(m1, n1, m2, n2, c): up, down, left, right = check_edges(m1, n1, m2, n2, c) case = (m1-m2)*(n1-n2) if case == 0: return (m1 == m2 and up) or (n1 == n2 and left) elif case > 0: return (up and right) or (down and left) else: return (up and left) or (down and right) def check_edges(m1, n1, m2, n2, c): up, down, left, right = [True]*4 for i in range(min(n1, n2), max(n1, n2)+1): if matrix[min(m1, m2)][i] not in ('.', c): up = False break for i in range(min(n1, n2), max(n1, n2)+1): if matrix[max(m1, m2)][i] not in ('.', c): down = False break for i in range(min(m1, m2), max(m1, m2)+1): if matrix[i][min(n1, n2)] not in ('.', c): left = False break for i in range(min(m1, m2), max(m1, m2)+1): if matrix[i][max(n1, n2)] not in ('.', c): right = False break return up, down, left, right m, n = map(int, input().split()) matrix = [] coordinates = {} for i in range(m): row = list(input()) matrix.append(row) for j in range(n): c = row[j] if c.isupper(): coordinates.setdefault(c, []).append((i, j)) result = [] friends = sorted(coordinates) i = 0 while i < len(friends): c = friends[i] if c in result or c == '.': i += 1 continue (m1, n1), (m2, n2) = coordinates[c] if find_route(m1, n1, m2, n2, c): result.append(c) friends[i] = '.' matrix[m1][n1] = '.' matrix[m2][n2] = '.' i = 0 continue i += 1 if len(result) == len(friends): print(''.join(result)) else: print('IMPOSSIBLE') # # 기존 프렌즈 사천성 -> 경로가 세 개 이하 선분 # # 리틀 프렌즈 -> 경로가 2개 이하의 수평/수직 선분 # # . 빈칸 / * 막힌칸 # from collections import defaultdict # from copy import deepcopy # def delete_line(a, b, board, key): # # 선분1 # x1, y1 = a # x2, y2 = b # check = True # # 같은 행 위치 # if x1 == x2: # for i in range(y1+1, y2): # if board[x1][i] != '.': # check = False # break # if check: # board[x1][y1], board[x2][y2] = '.', '.' # print(board) # return key # # 같은 열 위치 # elif y1 == y2: # for i in range(x1+1, x2): # if board[i][y1] != '.': # check = False # break # if check: # board[x1][y1], board[x2][y2] = '.', '.' # return key # # 선분2 # check1, check2 = True, True # # 왼쪽에 있는 경우 # if x1 < x2 and y1 > y2: # # 두 방향이 있음 # for i in range(y2, y1): # if board[x1][i] != '.': # check1 = False # break # if check1: # for i in range(x1, x2): # if board[i][y2] != '.': # check1 = False # break # for i in range(x1+1, x2+1): # if board[i][y1] != '.': # check2 = False # break # if check2: # for i in range(y2+1, y1+1): # if board[x2][i] != '.': # check2 = False # break # elif x1 < x2 and y1 < y2: # for i in range(y1+1, y2+1): # if board[x1][i] != '.': # check1 = False # break # if check1: # for i in range(x1, x2): # if board[i][y2] != '.': # check1 = False # break # for i in range(x1+1, x2+1): # if board[i][y1] != '.': # check2 = False # break # if check2: # for i in range(y1+1, y2): # if board[x2][i] != '.': # check2 = False # break # if check1 and check2: # board[x1][y1], board[x2][y2] = '.', '.' # return key # def solution(m, n, board): # answer = [] # board = list(map(list, board)) # positions = defaultdict(list) # for i in range(m): # for j in range(n): # if ord(board[i][j]) in list(range(ord('A'), ord('Z')+1)): # positions[board[i][j]].append((i, j)) # while True: # before_answer = deepcopy(answer) # temp = [] # for a, b in positions.values(): # t = delete_line(a, b, board, board[a[0]][a[1]]) # if t != None: # temp.append(t) # if temp: # answer.extend(sorted(temp)) # if len(answer) == len(positions): # return ''.join(answer) # else: # if before_answer == answer: # return "IMPOSSIBLE" # m = 3 # n = 3 # board = ['DBA', 'C*A', 'CDB'] # print(solution(m, n, board)) # a=[[1,2],[3,4]] # a[0][1] = 3 # print(a) # # 특정 문자 조건 찾기 # # print(list(range(ord('A'), ord('Z')+1))) # # 문자열 1개씩 가져오는지? # # print(board[0][0]) # # for v in 'abc': # # print(v) # # 문자열 부분 리스트로 변환하기 # # board = list(map(list, board)) # # board = [list(b) for b in board] # # print(board)

[ "dobi1115@gmail.com" ]

dobi1115@gmail.com

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/Chapter 3 Math, Function, Strings and Objects/commonPythonFunction.py

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padamcs36/Introduction_to_Python_By_Daniel

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refs/heads/main

2023-02-22T08:11:01.450054

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''' abs(), max(), min(), pow(), round() these are python built in functions there is no need to import separate module for them ''' print(abs(-3)) #return the value in positive always print(max(4,5,-8,0,7)) print(min(0,4,6,3,-4)) print(pow(4,3)) print(round(4.535)) print(round(5.554667, 2))

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/src/learningCurve/tenPercent/lrClassifierN.py

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no_license

TanemuraKiyoto/PPI-native-detection-via-LR

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2022-12-05T11:59:01.014309

2020-08-10T00:41:17

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# 9 September 2019 # Kiyoto Aramis Tanemura # I modified the rfClassifier.py script to implement a logistic regression classifier. This classifier runs faster than the random forest classifier and Jun previously observed comparable results between logistic regression and random forest classifiers for the protein folding system. Due to the lesser time cost, I may sample a greater hyperparameter space using the logistic regression classifier. If the sampling yields a region in which overfitting is not observed, then I can refine the search. If the results are similar to that of the random forest classifier, then I may have exhausted the dataset for generalizability. # Modified 26 October 2019 by Kiyoto Aramis Tanemura. Apply logistic regression classifier to CASF-PPI dataset. # Modified 2020-02-09 by KAT. Code generalized for public use on GitHub. import pandas as pd import numpy as np import os import json import pickle #from multiprocessing import Pool from time import time from sklearn.linear_model import LogisticRegression from sklearn.model_selection import RandomizedSearchCV from sklearn.preprocessing import StandardScaler from random import shuffle, random #os.chdir('/mnt/scratch/tanemur1/') toc = time() # Randomize input file orders pathToInput = 'data/comparison_descriptors/' pathToOutput = 'results/learningCurve/' fileNames = [x for x in os.listdir(pathToInput) if '.csv' in x] shuffle(fileNames) # note: shuffle is in-place. Do not assign to variable # Specify training set fraction train_fraction = 0.1 if len(fileNames) * train_fraction == int(len(fileNames) * train_fraction): train_file_number = int(len(fileNames) * train_fraction) else: train_file_number = int(len(fileNames) * train_fraction + 1) x_train = pd.DataFrame() y_train = pd.DataFrame() # Read individual csv for comparison descriptors, append to train_data, and partition to x_train, y_train fileNamesWithPath = [pathToInput + fileName for fileName in fileNames] def read_csv(filePath): return pd.read_csv(filePath, index_col = 0) print('begin read training set') #with Pool(np.min([train_file_number, 28])) as p: # train_dataList = list(p.map(read_csv, fileNamesWithPath[:train_file_number])) train_dataList = list(map(read_csv, fileNamesWithPath[:train_file_number])) print('begin append DF | ', (time() - toc) / 60, ' min') # Append DataFrames into one. While loop used to reduce append operations. Iteratively, DFs in a list are appended # to the following DF. while len(train_dataList) != 1: number = int(len(train_dataList) / 2) for i in range(number): train_dataList[2 * i] = train_dataList[2 * i].append(train_dataList[2 * i + 1], sort = True) for j in range(number): del train_dataList[j + 1] x_train = train_dataList[0] del train_dataList print('train_data dimensions', x_train.shape, ' | ', (time() - toc) / 60, ' min') y_train = x_train['class'] x_train = x_train.drop('class', axis = 1) # x_train contains only nonbonding descriptors feature_names = x_train.columns scaler = StandardScaler() scaler.fit(x_train) x_train = scaler.transform(x_train) y_train = y_train.values print('Dimensions x_train ', x_train.shape, ' | y_train', y_train.shape) # Define a logistic regression classifier along with pertinent hyperparameters. Here, default values are used. clf = LogisticRegression(penalty='l2', verbose = 1) def sampleRationalVals(minVal, maxVal): return 2 ** (random() * (np.log2(maxVal) - np.log2(minVal)) + np.log2(minVal)) def sampleRationalList(minVal, maxVal): theList = [] for i in range(int(2 * np.log2(maxVal - minVal) + 1)): theVal = sampleRationalVals(minVal, maxVal) theList.append(theVal) return theList parameters = { # include any hyperparameters to sample. Otherwise, leave empty to perform five fold cross validation with default values. For example: # 'C': sampleRationalList(0.001, 1000), # 'solver': ['newton-cg', 'lbfgs', 'sag','saga'] } print('begin RandomizedSearchCV | ' + str((time() - toc)/60) + ' mins') randomized_search = RandomizedSearchCV(estimator = clf, param_distributions = parameters, n_iter = 1, scoring = 'accuracy', refit = True, cv = 5, verbose = 1, n_jobs = 1, pre_dispatch = 'n_jobs', return_train_score=True) randomized_search.fit(x_train, y_train) print('begin output | ', (time() - toc) / 60 / 60, ' hours') tic = time() with open(pathToOutput + 'bestParamN.json', 'w') as g: json.dump(randomized_search.best_estimator_.get_params(), g) with open(pathToOutput + 'modelN.pkl', 'wb') as h: pickle.dump(randomized_search, h) with open(pathToOutput + 'trainingSetN.txt', 'w') as i: i.write('Training set:\n') for pdbID in fileNames[:train_file_number]: i.write(pdbID + '\n') i.write('\nJob time: ' + str((tic - toc) / 60 / 60) + ' hours') with open(pathToOutput + 'standardScalerN.pkl', 'wb') as j: pickle.dump(scaler, j) bestCoefficient = randomized_search.best_estimator_.coef_ coefDf = pd.DataFrame(bestCoefficient, columns = feature_names) with open(pathToOutput + 'coefficientsN.csv', 'w') as f: coefDf.to_csv(f)

[ "tanemur1@msu.edu" ]

tanemur1@msu.edu

bd9ed5751eee1c211f209fe86a475e63d9c97c2d

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/ClassExercise & studio/chapter 8/Ex.02 pass 7-04-2016.py

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SmileShmily/LaunchCode-summerofcode-Unit1

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2021-01-16T23:19:23.413010

2017-06-29T02:49:19

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''' ’ (GRADED) Write a function analyze_text that receives a string as input. Your function should count the number of alphabetic characters (a through z, or A through Z) in the text and also keep track of how many are the letter 'e' (upper or lowercase). Your function should return an analysis of the text, something like this: The text contains 243 alphabetic characters, of which 109 (44.8%) are ‘e’. ''' #analyze_text=input("Please enter your str:") def analyze_text(str): # your code here # lows="abcdefghijklmnopqrstuvwxyz" # ups="ABCDEFGHIJKLMNOPQRSTUVWXYZ" str = repr(str).lower() numberOfe = 0 totalChars = 0 for ch in str: if ((ch <= 'Z' and ch >= 'A') or (ch <= 'z' and ch >= 'a')): totalChars = totalChars + 1 if ch == 'e': numberOfe = numberOfe + 1 percent_with_e = (numberOfe/totalChars) * 100 return("The text contains %d alphabetic characters, of which %d (%.1f%) %sare 'e'."% (totalChars, numberOfe, percent_with_e)) # Don't copy these tests into Vocareum from test import testEqual str = "Eeeee" expected = "The text contains 5 alphabetic characters, of which 5 (100.0%) are 'e'." testEqual(analyze_text(str), expected) str = "Blueberries are tastee!" expected = "The text contains 20 alphabetic characters, of which 6 (30.0%) are 'e'." testEqual(analyze_text(str), expected) str = "Wright's book, Gadsby, contains a total of 0 of that most common symbol ;)" expected = "The text contains 55 alphabetic characters, of which 0 (0.0%) are 'e'." testEqual(analyze_text(str), expected) '''Output Pass Pass Pass'''

[ "zyxjyaya@gmail.com" ]

zyxjyaya@gmail.com

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sirajmuneer123/MITx-6.00.1x-Introduction-to-Computer-Science-and-Programming-Using-Python

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# Enter your code for NewsStory in this box #Part 1: Data Structure Design class NewsStory(object): def __init__(self, guid, title, subject, summary, link): self.guid = guid self.title = title self.subject = subject self.summary = summary self.link = link def getGuid(self): return self.guid def getTitle(self): return self.title def getSubject(self): return self.subject def getSummary(self): return self.summary def getLink(self): return self.link

[ "sirajmuneer4@gmail.com" ]

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2020-03-31T21:46:25.061571

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""" Модуль демонстрации строк документации. Пример использования смотрите в файле example_38.py """ def square(x): """ Функция принимает число и возвращает квадрат этого числа. """ return x ** 2

[ "zatonskaya@yandex.ru" ]

zatonskaya@yandex.ru

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/20.valid-parenthesis.py

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2022-11-29T13:16:03.474242

2020-08-11T19:06:07

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def isValid(s): stack=[] pairs={ '(':')', '[':']', '{':'}' } for char in s: if char in pairs: # storing corresponding closing parenthesis stack.append(pairs[char]) # print(stack) else: if not stack or stack.pop() != char: return False # print("Final=>",stack) return not stack print(isValid("()[{}]")) print(isValid("()[]{}")) # test=[] test=[1] # print(not test) # Return True if list is empty. Bcoz: empty = False. so not False= True # print(test)

[ "emailatmanash@gmail.com" ]

emailatmanash@gmail.com

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jschnab/data-structures-algos-python

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2022-12-27T17:56:34.622558

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import random def select(seq, start): min_idx = start for j in range(start + 1, len(seq)): if seq[j] < seq[min_idx]: min_idx = j return min_idx def selection_sort(seq): for i in range(len(seq) - 1): min_idx = select(seq, i) tmp = seq[i] seq[i] = seq[min_idx] seq[min_idx] = tmp def merge(seq, start, mid, stop): lst = [] i = start j = mid # merge the two lists while each has more elements while i < mid and j < stop: if seq[i] < seq[j]: lst.append(seq[i]) i += 1 else: lst.append(seq[j]) j += 1 # copy in the rest of the start-to-mid sequence while i < mid: lst.append(seq[i]) i += 1 # no need to copy the rest of the sequence from j to stop # the next part of the code does this for us # so no need to do: # while j < stop: # lst.append(seq[j]) # j += 1 # copy elements back to the original sequence for i in range(len(lst)): seq[start + i] = lst[i] def merge_sort_recursive(seq, start, stop): # >= is necessary if sequence is empty # otherwise start == stop - 1 does the job if start >= stop - 1: return mid = (start + stop) // 2 merge_sort_recursive(seq, start, mid) merge_sort_recursive(seq, mid, stop) merge(seq, start, mid, stop) def merge_sort(seq): merge_sort_recursive(seq, 0, len(seq)) def partition(seq, start, stop): # pivot_index comes from the start location in the list pivot_index = start pivot = seq[pivot_index] i = start + 1 j = stop - 1 while i <= j: while i <= j and seq[i] <= pivot: i += 1 while i <= j and seq[j] > pivot: j -= 1 if i < j: tmp = seq[i] seq[i] = seq[j] seq[j] = tmp i += 1 j -= 1 seq[pivot_index] = seq[j] seq[j] = pivot return j def quicksort_recursive(seq, start, stop): if start >= stop - 1: return # pivot index ends up between the two halves # where the pivot value is in its final location pivot_index = partition(seq, start, stop) quicksort_recursive(seq, start, pivot_index) quicksort_recursive(seq, pivot_index + 1, stop) def quicksort(seq): # randomize sequence to find a good pivot for i in range(len(seq)): j = random.randint(0, len(seq) - 1) seq[i], seq[j] = seq[j], seq[i] quicksort_recursive(seq, 0, len(seq)) if __name__ == "__main__": seq = [random.randint(0, 100) for _ in range(10)] print("Before sort:", seq) quicksort(seq) print("After sort:", seq)

[ "jonathan.schnabel31@gmail.com" ]

jonathan.schnabel31@gmail.com

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dr-dos-ok/Code_Jam_Webscraper

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import sys import re firstline = sys.stdin.readline() (L, D, N) = map(int, firstline.split()) lex = [] for x in range(D): lex.append(sys.stdin.readline()) lex = ''.join(lex) for (i, pattern) in enumerate(sys.stdin.readlines()): pattern = pattern.replace('(','[').replace(')',']') matches = re.findall(pattern, lex) print 'Case #%d: %d' % (i+1, len(matches))

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miliar1732@gmail.com

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/exercicios-secao08/exercicio29.py

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from math import factorial, radians def sinh(graus: float) -> float: soma: float = 0.0 x: float = radians(graus) for n in range(6): soma += (x ** (2 * n + 1)) / factorial(2 * n + 1) return soma

[ "davi.miau@gmail.com" ]

davi.miau@gmail.com

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/app.py

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bossnode/rufo-mp3-fetcher

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2020-06-10T04:11:09.257754

2019-06-26T20:25:12

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import gi gi.require_version('Gtk', '3.0') from gi.repository import Gtk import os, sys from soundspider import SoundSpider from time import sleep import threading class Handler: def onDestroy(self, *args): try: download_thread._stop() except: pass Gtk.main_quit() def onToggleDownload(self, button): status = "Downloading..." builder.get_object('label4').set_text(status) button.set_sensitive(False) builder.get_object("folder_label").set_sensitive(False) builder.get_object("url_label").set_sensitive(False) ## verbose? # verbose = True verbose = False params = (builder.get_object("url_label").get_text(),builder.get_object("folder_label").get_text(),verbose, builder.get_object('label4'), button,builder.get_object("url_label"),builder.get_object("folder_label")) download_thread = threading.Thread(target=SoundSpider.convert, args=params) download_thread.start() return def resource_path(relative_path): """ Get absolute path to resource, works for dev and for PyInstaller """ try: # PyInstaller creates a temp folder and stores path in _MEIPASS base_path = sys._MEIPASS except Exception: base_path = os.path.abspath(".") return os.path.join(base_path, relative_path) # """ Get absolute path to resource, works for dev and for PyInstaller """ # base_path = getattr(sys, '_MEIPASS', os.path.dirname(os.path.abspath(__file__))) # return os.path.join(base_path, relative_path) download_thread = threading.Thread() builder = Gtk.Builder() builder.add_from_file(resource_path("ui.glade")) builder.connect_signals(Handler()) window = builder.get_object("window1") window.show_all() Gtk.main()

[ "=" ]

=

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HYLee1008/Python

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2022-12-12T12:07:49.198551

2020-09-05T12:41:55

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### Reverse linked list by iterative ### Iterative consumes 70% memory of the recursive method. And slightly faster. from datastructure import * def reverse_list(head): node, prev = head, None while node: next, node.next = node.next, prev node, prev = next, node return prev input = ListNode(1) input.next = ListNode(2) input.next.next = ListNode(3) input.next.next.next = ListNode(4) input.next.next.next.next = ListNode(5) reverse = reverse_list(input) while reverse: print(reverse.val) reverse = reverse.next

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discone1008@gmail.com

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/etc/openshift_clean.py

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doaa-altarawy/quokka

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refs/heads/development

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#!/usr/bin/python """ THIS SCRIPT CLEANS ALL DATA IN YOUR QUOKKA DB RUN ONLY IN OPENSHIFT DEMO DEPLOY OR AT YOUR OWN RISK!!!! """ from quokka import create_app from quokka.core.models.content import Content from quokka.core.models.config import Config from quokka.core.models.channel import Channel from quokka.modules.accounts.models import User app = create_app() Content.objects.delete() User.objects.delete() Config.objects.delete() for channel in Channel.objects.filter(parent__ne=None): channel.delete() Channel.objects.delete()

[ "rochacbruno@gmail.com" ]

rochacbruno@gmail.com

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/setup.py

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loum/baip-loader

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2021-01-25T07:39:34.190887

2015-05-05T00:15:21

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""":mod:docutils` setup.py file to generate Python compatible sources in build/ directory """ import os import glob import fnmatch import shutil from setuptools import setup VERSION = '0.0.0' def opj(*args): path = os.path.join(*args) return os.path.normpath(path) def find_data_files(srcdir, *wildcards, **kw): """Get a list of all files under the *srcdir* matching *wildcards*, returned in a format to be used for install_data. """ def walk_helper(arg, dirname, files): names = [] lst, wildcards = arg for wildcard in wildcards: wc_name = opj(dirname, wildcard) for current_file in files: filename = opj(dirname, current_file) if (fnmatch.fnmatch(filename, wc_name) and not os.path.isdir(filename)): if kw.get('version') is None: names.append(filename) else: versioned_file = '%s.%s' % (filename, kw.get('version')) shutil.copyfile(filename, versioned_file) names.append('%s.%s' % (filename, kw.get('version'))) if names: if kw.get('target_dir') is None: lst.append(('', names)) else: lst.append((kw.get('target_dir'), names)) file_list = [] recursive = kw.get('recursive', True) if recursive: os.path.walk(srcdir, walk_helper, (file_list, wildcards)) else: walk_helper((file_list, wildcards), srcdir, [os.path.basename(current_file) for current_file in glob.glob(opj(srcdir, '*'))]) return file_list find_data_files('baip_loader/conf/', '*.conf', version=VERSION) setup(name='python-baip-loader', version=VERSION, description='BAIP-Loader', author='Lou Markovski', author_email='lou.markovski@gmail.com', url='', scripts=['baip_loader/bin/baip-loader'], packages=['baip_loader', 'baip_loader.config'], package_data={'baip_loader': ['conf/*.conf.[0-9]*.[0-9]*.[0-9]*']})

[ "lou.markovski@gmail.com" ]

lou.markovski@gmail.com

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/ProjectApplication/grant_management/migrations/0030_renames_media_to_medium.py

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[ "CC-BY-NC-SA-4.0", "CC-BY-SA-4.0", "CC-BY-4.0", "MIT" ]

permissive

Swiss-Polar-Institute/project-application

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refs/heads/master

2023-08-31T04:01:23.492272

2023-08-25T14:33:02

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# Generated by Django 3.0.5 on 2020-05-12 10:39 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('project_core', '0118_calls_need_to_be_part_of_a_funding_instrument'), ('grant_management', '0029_signed_by_multiple_people'), ] operations = [ migrations.RenameModel( old_name='Media', new_name='Medium', ), migrations.AlterField( model_name='grantagreement', name='signed_by', field=models.ManyToManyField(blank=True, help_text='People who signed the grant agreement', to='project_core.PhysicalPerson'), ), ]

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carles@pina.cat

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/benchmark/omninote/testcase/firstcases/testcase10_018.py

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Prefest2018/Prefest

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2021-12-09T19:36:24.554864

2021-12-06T12:46:14

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#coding=utf-8 import os import subprocess import time import traceback from appium import webdriver from appium.webdriver.common.touch_action import TouchAction from selenium.common.exceptions import NoSuchElementException, WebDriverException desired_caps = { 'platformName' : 'Android', 'deviceName' : 'Android Emulator', 'platformVersion' : '4.4', 'appPackage' : 'it.feio.android.omninotes', 'appActivity' : 'it.feio.android.omninotes.MainActivity', 'resetKeyboard' : True, 'androidCoverage' : 'it.feio.android.omninotes/it.feio.android.omninotes.JacocoInstrumentation', 'noReset' : True } def command(cmd, timeout=5): p = subprocess.Popen(cmd, stderr=subprocess.STDOUT, stdout=subprocess.PIPE, shell=True) time.sleep(timeout) p.terminate() return def getElememt(driver, str) : for i in range(0, 5, 1): try: element = driver.find_element_by_android_uiautomator(str) except NoSuchElementException: time.sleep(1) else: return element os.popen("adb shell input tap 50 50") element = driver.find_element_by_android_uiautomator(str) return element def getElememtBack(driver, str1, str2) : for i in range(0, 2, 1): try: element = driver.find_element_by_android_uiautomator(str1) except NoSuchElementException: time.sleep(1) else: return element for i in range(0, 5, 1): try: element = driver.find_element_by_android_uiautomator(str2) except NoSuchElementException: time.sleep(1) else: return element os.popen("adb shell input tap 50 50") element = driver.find_element_by_android_uiautomator(str2) return element def swipe(driver, startxper, startyper, endxper, endyper) : size = driver.get_window_size() width = size["width"] height = size["height"] try: driver.swipe(start_x=int(width * startxper), start_y=int(height * startyper), end_x=int(width * endxper), end_y=int(height * endyper), duration=2000) except WebDriverException: time.sleep(1) driver.swipe(start_x=int(width * startxper), start_y=int(height * startyper), end_x=int(width * endxper), end_y=int(height * endyper), duration=2000) return # testcase018 try : starttime = time.time() driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps) element = getElememtBack(driver, "new UiSelector().text(\"Nothing here!\")", "new UiSelector().className(\"android.widget.TextView\").instance(3)") TouchAction(driver).tap(element).perform() element = getElememt(driver, "new UiSelector().resourceId(\"it.feio.android.omninotes:id/menu_sort\").className(\"android.widget.TextView\")") TouchAction(driver).long_press(element).release().perform() element = getElememt(driver, "new UiSelector().resourceId(\"it.feio.android.omninotes:id/menu_sort\").className(\"android.widget.TextView\")") TouchAction(driver).long_press(element).release().perform() element = getElememt(driver, "new UiSelector().resourceId(\"it.feio.android.omninotes:id/menu_sort\").className(\"android.widget.TextView\")") TouchAction(driver).long_press(element).release().perform() element = getElememtBack(driver, "new UiSelector().text(\"Nothing here!\")", "new UiSelector().className(\"android.widget.TextView\").instance(3)") TouchAction(driver).tap(element).perform() element = getElememt(driver, "new UiSelector().className(\"android.widget.ImageView\").description(\"More options\")") TouchAction(driver).tap(element).perform() element = getElememtBack(driver, "new UiSelector().text(\"Reduced view\")", "new UiSelector().className(\"android.widget.TextView\")") TouchAction(driver).tap(element).perform() element = getElememt(driver, "new UiSelector().resourceId(\"it.feio.android.omninotes:id/menu_search\").className(\"android.widget.TextView\")") TouchAction(driver).tap(element).perform() except Exception, e: print 'FAIL' print 'str(e):\t\t', str(e) print 'repr(e):\t', repr(e) print traceback.format_exc() else: print 'OK' finally: cpackage = driver.current_package endtime = time.time() print 'consumed time:', str(endtime - starttime), 's' command("adb shell am broadcast -a com.example.pkg.END_EMMA --es name \"10_018\"") jacocotime = time.time() print 'jacoco time:', str(jacocotime - endtime), 's' driver.quit() if (cpackage != 'it.feio.android.omninotes'): cpackage = "adb shell am force-stop " + cpackage os.popen(cpackage)

[ "prefest2018@gmail.com" ]

prefest2018@gmail.com

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/addons/account/tests/test_tax.py

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[]

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gahan-corporation/wyatt

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7,285

py

from gerp.addons.account.tests.account_test_users import AccountTestUsers import time class TestTax(AccountTestUsers): def setUp(self): super(TestTax, self).setUp() self.fixed_tax = self.tax_model.create({ 'name': "Fixed tax", 'amount_type': 'fixed', 'amount': 10, 'sequence': 1, }) self.fixed_tax_bis = self.tax_model.create({ 'name': "Fixed tax bis", 'amount_type': 'fixed', 'amount': 15, 'sequence': 2, }) self.percent_tax = self.tax_model.create({ 'name': "Percent tax", 'amount_type': 'percent', 'amount': 10, 'sequence': 3, }) self.division_tax = self.tax_model.create({ 'name': "Division tax", 'amount_type': 'division', 'amount': 10, 'sequence': 4, }) self.group_tax = self.tax_model.create({ 'name': "Group tax", 'amount_type': 'group', 'amount': 0, 'sequence': 5, 'children_tax_ids': [ (4, self.fixed_tax.id, 0), (4, self.percent_tax.id, 0) ] }) self.group_tax_bis = self.tax_model.create({ 'name': "Group tax bis", 'amount_type': 'group', 'amount': 0, 'sequence': 6, 'children_tax_ids': [ (4, self.fixed_tax.id, 0), (4, self.percent_tax.id, 0) ] }) self.group_of_group_tax = self.tax_model.create({ 'name': "Group of group tax", 'amount_type': 'group', 'amount': 0, 'sequence': 7, 'children_tax_ids': [ (4, self.group_tax.id, 0), (4, self.group_tax_bis.id, 0) ] }) self.bank_journal = self.env['account.journal'].search([('type', '=', 'bank'), ('company_id', '=', self.account_manager.company_id.id)])[0] self.bank_account = self.bank_journal.default_debit_account_id self.expense_account = self.env['account.account'].search([('user_type_id.type', '=', 'payable')], limit=1) #Should be done by onchange later def test_tax_group_of_group_tax(self): self.fixed_tax.include_base_amount = True self.group_tax.include_base_amount = True self.group_of_group_tax.include_base_amount = True res = self.group_of_group_tax.compute_all(200.0) self.assertEquals(res['total_excluded'], 200.0) # After calculation of first group # base = 210 # total_included = 231 # Base of the first grouped is passed # Base after the second group (220) is dropped. # Base of the group of groups is passed out, # so we obtain base as after first group self.assertEquals(res['base'], 210.0) self.assertEquals(res['total_included'], 263.0) def test_tax_group(self): res = self.group_tax.compute_all(200.0) self.assertEquals(res['total_excluded'], 200.0) self.assertEquals(res['total_included'], 230.0) self.assertEquals(len(res['taxes']), 2) self.assertEquals(res['taxes'][0]['amount'], 10.0) self.assertEquals(res['taxes'][1]['amount'], 20.0) def test_tax_percent_division(self): self.division_tax.price_include = True self.division_tax.include_base_amount = True self.percent_tax.price_include = False self.percent_tax.include_base_amount = False res_division = self.division_tax.compute_all(200.0) res_percent = self.percent_tax.compute_all(200.0) self.assertEquals(res_division['taxes'][0]['amount'], 20.0) self.assertEquals(res_percent['taxes'][0]['amount'], 20.0) self.division_tax.price_include = False self.division_tax.include_base_amount = False self.percent_tax.price_include = True self.percent_tax.include_base_amount = True res_division = self.division_tax.compute_all(200.0) res_percent = self.percent_tax.compute_all(200.0) self.assertEquals(res_division['taxes'][0]['amount'], 22.22) self.assertEquals(res_percent['taxes'][0]['amount'], 18.18) def test_tax_sequence_normalized_set(self): self.division_tax.sequence = 1 self.fixed_tax.sequence = 2 self.percent_tax.sequence = 3 taxes_set = (self.group_tax | self.division_tax) res = taxes_set.compute_all(200.0) self.assertEquals(res['taxes'][0]['amount'], 22.22) self.assertEquals(res['taxes'][1]['amount'], 10.0) self.assertEquals(res['taxes'][2]['amount'], 20.0) def test_tax_include_base_amount(self): self.fixed_tax.include_base_amount = True res = self.group_tax.compute_all(200.0) self.assertEquals(res['total_included'], 231.0) def test_tax_currency(self): self.division_tax.amount = 15.0 res = self.division_tax.compute_all(200.0, currency=self.env.ref('base.VEF')) self.assertAlmostEqual(res['total_included'], 235.2941) def test_tax_move_lines_creation(self): """ Test that creating a move.line with tax_ids generates the tax move lines and adjust line amount when a tax is price_include """ self.fixed_tax.price_include = True self.fixed_tax.include_base_amount = True company_id = self.env['res.users'].browse(self.env.uid).company_id.id vals = { 'date': time.strftime('%Y-01-01'), 'journal_id': self.bank_journal.id, 'name': 'Test move', 'line_ids': [(0, 0, { 'account_id': self.bank_account.id, 'debit': 235, 'credit': 0, 'name': 'Bank Fees', 'partner_id': False, }), (0, 0, { 'account_id': self.expense_account.id, 'debit': 0, 'credit': 200, 'date': time.strftime('%Y-01-01'), 'name': 'Bank Fees', 'partner_id': False, 'tax_ids': [(4, self.group_tax.id), (4, self.fixed_tax_bis.id)] })], 'company_id': company_id, } move = self.env['account.move'].with_context(apply_taxes=True).create(vals) aml_fixed_tax = move.line_ids.filtered(lambda l: l.tax_line_id.id == self.fixed_tax.id) aml_percent_tax = move.line_ids.filtered(lambda l: l.tax_line_id.id == self.percent_tax.id) aml_fixed_tax_bis = move.line_ids.filtered(lambda l: l.tax_line_id.id == self.fixed_tax_bis.id) self.assertEquals(len(aml_fixed_tax), 1) self.assertEquals(aml_fixed_tax.credit, 10) self.assertEquals(len(aml_percent_tax), 1) self.assertEquals(aml_percent_tax.credit, 20) self.assertEquals(len(aml_fixed_tax_bis), 1) self.assertEquals(aml_fixed_tax_bis.credit, 15) aml_with_taxes = move.line_ids.filtered(lambda l: set(l.tax_ids.ids) == set([self.group_tax.id, self.fixed_tax_bis.id])) self.assertEquals(len(aml_with_taxes), 1) self.assertEquals(aml_with_taxes.credit, 190)

[ "duchess@gahan-corporation.com" ]

duchess@gahan-corporation.com

1ff24ffb45f8546c93fbec4517976b96ca01b0bc

b8ed71f3d1a36c119d846e97f1aa7d8ba6774f52

/680_Valid_Palindrome_II.py

5dd32bf280843101a247fdd621ab833fcc2b7d1b

[]

no_license

imjaya/Leetcode_solved

0831c4114dd919864452430c4e46d3f69b4bd0cd

374eb0f23ae14d9638d20bbfe622209f71397ae0

refs/heads/master

2023-05-24T17:57:56.633611

2023-05-16T06:31:42

284,203,426

0

null

UTF-8

Python

false

491

py

def helper(s,l,r): while l<r: if(s[l]!=s[r]): return False l+=1 r-=1 return True class Solution: def validPalindrome(self, s: str) -> bool: left=0 right=len(s)-1 while(left<right): if(s[left]!=s[right]): return helper(s,left+1,right) or helper(s,left,right-1) else: left+=1 right-=1 return True

[ "smjayasurya1997@gmail.com" ]

smjayasurya1997@gmail.com

c335ae67050596c16c4e388d411d18e7b88ca797

863a7b075963c2882d9fe5df66af16c6e52576a9

/deepiu/textsim/evaluate/evaluate-sim.py

2079a1cc158d696d4cf173579d1afde74c720102

[]

no_license

buptpriswang/hasky

3c3510d43821bbdfdfa216a337cde6e0747b3423

93afdc32956643fe191fcf1a5aa635570e219ab0

refs/heads/master

2021-06-30T19:45:03.329238

2017-09-22T15:41:58

null

0

null

UTF-8

Python

false

3,532

py

#!/usr/bin/env python # -*- coding: utf-8 -*- # ============================================================================== # \file evaluate-sim-score.py # \author chenghuige # \date 2016-09-25 00:46:53.890615 # \Description # ============================================================================== from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf flags = tf.app.flags FLAGS = flags.FLAGS flags.DEFINE_string('model_dir', '/home/gezi/new/temp/makeup/title2name/model/bow/', '') #flags.DEFINE_string('model_dir', '/home/gezi/new/temp/makeup/title2name/model/cnn.hic/', '') flags.DEFINE_string('exact_model_dir', '/home/gezi/new/temp/makeup/title2name/model/bow.elementwise/', '') flags.DEFINE_string('vocab', '/home/gezi/new/temp/makeup/title2name/tfrecord/seq-basic/vocab.txt', '') flags.DEFINE_bool('use_exact_predictor', False, '') flags.DEFINE_string('key', 'score', '') flags.DEFINE_string('lkey', 'dual_bow/main/ltext:0', '') flags.DEFINE_string('rkey', 'dual_bow/main/rtext:0', '') #flags.DEFINE_string('lkey', 'dual_cnn/main/ltext:0', '') #flags.DEFINE_string('rkey', 'dual_cnn/main/rtext:0', '') flags.DEFINE_string('exact_key', 'score', '') flags.DEFINE_string('exact_lkey', 'dual_bow2/main/ltext:0', '') flags.DEFINE_string('exact_rkey', 'dual_bow2/main/rtext:0', '') flags.DEFINE_float('exact_ratio', 1., '') flags.DEFINE_integer('np_seed', 1024, '0 random otherwise fixed random') import sys import numpy as np import melt logging = melt.logging import gezi from deepiu.util import evaluator from deepiu.util import algos_factory class Predictor(melt.PredictorBase): def __init__(self, model_dir, key, lkey, rkey, index=0): self._predictor = melt.Predictor(model_dir) self._key = key self._lkey = lkey self._rkey = rkey self._index = index def predict(self, ltext, rtext): score = self._predictor.inference(self._key, feed_dict= { self._lkey: ltext, self._rkey: rtext }, index=self._index ) return score def evaluate_score(): evaluator.init() text_max_words = evaluator.all_distinct_texts.shape[1] print('text_max_words:', text_max_words) predictor = Predictor(FLAGS.model_dir, FLAGS.key, FLAGS.lkey, FLAGS.rkey, index=0) exact_predictor=None if FLAGS.use_exact_predictor: exact_predictor = Predictor(FLAGS.exact_model_dir, FLAGS.exact_key, FLAGS.exact_lkey, FLAGS.exact_rkey, index=-1) print(tf.get_collection(FLAGS.key)) seed = FLAGS.np_seed if FLAGS.np_seed else None index = evaluator.random_predict_index(seed=seed) evaluator.evaluate_scores(predictor, random=True, index=index) if exact_predictor is not None: ##well for seq2seq did experiment and for makeup title2name score(average time per step) is much better then ori_score ##so just juse score will be fine #exact_predictor._key = 'ori_score' #evaluator.evaluate_scores(predictor, random=True, exact_predictor=exact_predictor, index=index) #exact_predictor._key = 'score' evaluator.evaluate_scores(predictor, random=True, exact_predictor=exact_predictor, exact_ratio=FLAGS.exact_ratio, index=index) def main(_): logging.init(logtostderr=True, logtofile=False) evaluate_score() if __name__ == '__main__': tf.app.run()

[ "29109317@qq.com" ]

29109317@qq.com

8b7320fbb782d353ece0bf32dd2977b744b8acd8

0e1e643e864bcb96cf06f14f4cb559b034e114d0

/Exps_7_v3/I_to_M_Gk3_no_pad/pyramid_2side/bce_s001_tv_s0p1_L8/step11_L2345678.py

c03824dab2e889ccb93f4ca311d98915db768bee

[]

no_license

KongBOy/kong_model2

33a94a9d2be5b0f28f9d479b3744e1d0e0ebd307

1af20b168ffccf0d5293a393a40a9fa9519410b2

refs/heads/master

2022-10-14T03:09:22.543998

2022-10-06T11:33:42

242,080,692

3

0

null

UTF-8

Python

false

4,986

py

############################################################################################################################################################################################################# ############################################################################################################################################################################################################# ### 把 kong_model2 加入 sys.path import os code_exe_path = os.path.realpath(__file__) ### 目前執行 step10_b.py 的 path code_exe_path_element = code_exe_path.split("\\") ### 把 path 切分等等要找出 kong_model 在第幾層 kong_layer = code_exe_path_element.index("kong_model2") ### 找出 kong_model2 在第幾層 kong_model2_dir = "\\".join(code_exe_path_element[:kong_layer + 1]) ### 定位出 kong_model2 的 dir import sys ### 把 kong_model2 加入 sys.path sys.path.append(kong_model2_dir) # print(__file__.split("\\")[-1]) # print(" code_exe_path:", code_exe_path) # print(" code_exe_path_element:", code_exe_path_element) # print(" kong_layer:", kong_layer) # print(" kong_model2_dir:", kong_model2_dir) ############################################################################################################################################################################################################### # 按F5執行時，如果不是在 step10_b.py 的資料夾，自動幫你切過去～才可 import step10_a.py 喔！ code_exe_dir = os.path.dirname(code_exe_path) ### 目前執行 step10_b.py 的 dir if(os.getcwd() != code_exe_dir): ### 如果不是在 step10_b.py 的資料夾，自動幫你切過去～ os.chdir(code_exe_dir) # print("current_path:", os.getcwd()) ############################################################################################################################################################################################################### import Exps_7_v3.I_to_M_Gk3_no_pad.pyramid_0side.bce_s001_tv_s0p1_L8.step10_a as L8_0side import Exps_7_v3.I_to_M_Gk3_no_pad.pyramid_1side.bce_s001_tv_s0p1_L8.step10_a as L8_1side import step10_a as side2 ################################################################################################################################################################################################################################################################################################################################################################################################# ch032_1side_1__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_1__2side_1, ] ch032_1side_2__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_2__2side_1, side2.ch032_1side_2__2side_2, ] ch032_1side_3__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_3__2side_1, side2.ch032_1side_3__2side_2, side2.ch032_1side_3__2side_3, ] ch032_1side_4__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_4__2side_1, side2.ch032_1side_4__2side_2, side2.ch032_1side_4__2side_3, side2.ch032_1side_4__2side_4, ] ch032_1side_5__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_5__2side_1, side2.ch032_1side_5__2side_2, side2.ch032_1side_5__2side_3, side2.ch032_1side_5__2side_4, side2.ch032_1side_5__2side_5, ] ch032_1side_6__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_6__2side_1, side2.ch032_1side_6__2side_2, side2.ch032_1side_6__2side_3, side2.ch032_1side_6__2side_4, side2.ch032_1side_6__2side_5, side2.ch032_1side_6__2side_6, ] ch032_1side_7__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_7__2side_1, side2.ch032_1side_7__2side_2, side2.ch032_1side_7__2side_3, side2.ch032_1side_7__2side_4, side2.ch032_1side_7__2side_5, side2.ch032_1side_7__2side_6, side2.ch032_1side_7__2side_7, ] ch032_1side_8__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_8__2side_1, side2.ch032_1side_8__2side_2, side2.ch032_1side_8__2side_3, side2.ch032_1side_8__2side_4, side2.ch032_1side_8__2side_5, side2.ch032_1side_8__2side_6, side2.ch032_1side_8__2side_7, side2.ch032_1side_8__2side_8, ] ch032_1side_9__2side_all = [ L8_0side.ch032_0side, L8_1side.ch032_1side_1, side2.ch032_1side_9__2side_1, side2.ch032_1side_9__2side_2, side2.ch032_1side_9__2side_3, side2.ch032_1side_9__2side_4, side2.ch032_1side_9__2side_5, side2.ch032_1side_9__2side_6, side2.ch032_1side_9__2side_7, side2.ch032_1side_9__2side_8, side2.ch032_1side_9__2side_9, ] ch032_1side_all__2side_all = [ ch032_1side_1__2side_all, ch032_1side_2__2side_all, ch032_1side_3__2side_all, ch032_1side_4__2side_all, ch032_1side_5__2side_all, ch032_1side_6__2side_all, ch032_1side_7__2side_all, ch032_1side_8__2side_all, ch032_1side_9__2side_all, ]

[ "s89334roy@yahoo.com.tw" ]

s89334roy@yahoo.com.tw

930d498a17db90721c75d65299f8f10b0549e799

4a88daea1741ed6b5b5088b8d1f2787093abdf80

/tests/test_gen_couroutine.py

16e6479cc1bbc400493e0975a2f4a4ccec8b11d3

[ "MIT" ]

permissive

Nigelzhf/torweb

8e0bfeb6793ae9e50230e6b7b6284ec5e6da0d57

6859a878c126addb74410e872307ac9399f20eb7

refs/heads/master

2021-01-12T14:16:10.474945

2016-10-03T20:47:25

69,928,142

0

1

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2016-10-04T02:25:34

2016-10-04T02:25:33

null

UTF-8

Python

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414

py

#encoding:utf-8 import sys, os sys.path.append(os.path.dirname(sys.path[0])) from tornado.httpclient import AsyncHTTPClient from tornado import gen import tornado.ioloop @gen.coroutine def fetch_coroutine(url): http_client = AsyncHTTPClient() response = yield http_client.fetch(url) print('test') print(response) # fetch_coroutine('http://sxu.today') tornado.ioloop.IOLoop.instance().start()

[ "jmpews@gmail.com" ]

jmpews@gmail.com

8edd25a05553c2dfeaaf20dd6357cab4c4a87d07

4b5173af602439cdca0db985dcbdd25aef9b7a6b

/bin/topology-json-connector.py

fb1c33926b316f0d4ed9f1c45d8fbaeac5353af5

[]

no_license

kevangel79/argo-egi-connectors

a3d4bf502708cdce08acf01b5c58812042e4d201

dff42c3d4e5e7ea31ca839dd93f975ea27f4ffda

refs/heads/master

2022-02-23T15:01:13.081358

2022-02-15T14:54:05

250,012,827

0

null

2020-03-25T15:14:01

2020-03-25T15:14:00

null

UTF-8

Python

false

7,746

py

#!/usr/bin/python3 import argparse import os import sys import json import uvloop import asyncio from argo_egi_connectors.io.http import SessionWithRetry from argo_egi_connectors.exceptions import ConnectorHttpError, ConnectorParseError from argo_egi_connectors.io.webapi import WebAPI from argo_egi_connectors.io.avrowrite import AvroWriter from argo_egi_connectors.io.statewrite import state_write from argo_egi_connectors.log import Logger from argo_egi_connectors.config import Global, CustomerConf from argo_egi_connectors.utils import filename_date, datestamp, date_check from argo_egi_connectors.parse.flat_topology import ParseFlatEndpoints, ParseContacts from argo_egi_connectors.mesh.contacts import attach_contacts_topodata from urllib.parse import urlparse logger = None globopts = {} custname = '' def is_feed(feed): data = urlparse(feed) if not data.netloc: return False else: return True async def send_webapi(webapi_opts, data, topotype, fixed_date=None): webapi = WebAPI(sys.argv[0], webapi_opts['webapihost'], webapi_opts['webapitoken'], logger, int(globopts['ConnectionRetry'.lower()]), int(globopts['ConnectionTimeout'.lower()]), int(globopts['ConnectionSleepRetry'.lower()]), date=fixed_date) await webapi.send(data, topotype) def get_webapi_opts(cglob, confcust): webapi_custopts = confcust.get_webapiopts() webapi_opts = cglob.merge_opts(webapi_custopts, 'webapi') webapi_complete, missopt = cglob.is_complete(webapi_opts, 'webapi') if not webapi_complete: logger.error('Customer:%s %s options incomplete, missing %s' % (logger.customer, 'webapi', ' '.join(missopt))) raise SystemExit(1) return webapi_opts async def fetch_data(feed): remote_topo = urlparse(feed) session = SessionWithRetry(logger, custname, globopts) res = await session.http_get('{}://{}{}'.format(remote_topo.scheme, remote_topo.netloc, remote_topo.path)) return res def parse_source_topo(res, uidservtype, fetchtype): # group_groups, group_endpoints = ParseEoscTopo(logger, res, uidservtype, fetchtype).get_data() topo = ParseFlatEndpoints(logger, res, custname, uidservtype, fetchtype, scope=custname) group_groups = topo.get_groupgroups() group_endpoints = topo.get_groupendpoints() return group_groups, group_endpoints async def write_state(confcust, fixed_date, state): cust = list(confcust.get_customers())[0] jobstatedir = confcust.get_fullstatedir(globopts['InputStateSaveDir'.lower()], cust) fetchtype = confcust.get_topofetchtype() if fixed_date: await state_write(sys.argv[0], jobstatedir, state, globopts['InputStateDays'.lower()], fixed_date.replace('-', '_')) else: await state_write(sys.argv[0], jobstatedir, state, globopts['InputStateDays'.lower()]) def write_avro(confcust, group_groups, group_endpoints, fixed_date): custdir = confcust.get_custdir() if fixed_date: filename = filename_date(logger, globopts['OutputTopologyGroupOfGroups'.lower()], custdir, fixed_date.replace('-', '_')) else: filename = filename_date(logger, globopts['OutputTopologyGroupOfGroups'.lower()], custdir) avro = AvroWriter(globopts['AvroSchemasTopologyGroupOfGroups'.lower()], filename) ret, excep = avro.write(group_groups) if not ret: logger.error('Customer:%s : %s' % (logger.customer, repr(excep))) raise SystemExit(1) if fixed_date: filename = filename_date(logger, globopts['OutputTopologyGroupOfEndpoints'.lower()], custdir, fixed_date.replace('-', '_')) else: filename = filename_date(logger, globopts['OutputTopologyGroupOfEndpoints'.lower()], custdir) avro = AvroWriter(globopts['AvroSchemasTopologyGroupOfEndpoints'.lower()], filename) ret, excep = avro.write(group_endpoints) if not ret: logger.error('Customer:%s : %s' % (logger.customer, repr(excep))) raise SystemExit(1) def main(): global logger, globopts, confcust parser = argparse.ArgumentParser(description="""Fetch and construct entities from EOSC-PORTAL feed""") parser.add_argument('-c', dest='custconf', nargs=1, metavar='customer.conf', help='path to customer configuration file', type=str, required=False) parser.add_argument('-g', dest='gloconf', nargs=1, metavar='global.conf', help='path to global configuration file', type=str, required=False) parser.add_argument('-d', dest='date', metavar='YEAR-MONTH-DAY', help='write data for this date', type=str, required=False) args = parser.parse_args() group_endpoints, group_groups = list(), list() logger = Logger(os.path.basename(sys.argv[0])) fixed_date = None if args.date and date_check(args.date): fixed_date = args.date confpath = args.gloconf[0] if args.gloconf else None cglob = Global(sys.argv[0], confpath) globopts = cglob.parse() confpath = args.custconf[0] if args.custconf else None confcust = CustomerConf(sys.argv[0], confpath) confcust.parse() confcust.make_dirstruct() confcust.make_dirstruct(globopts['InputStateSaveDir'.lower()]) global custname custname = confcust.get_custname() # safely assume here one customer defined in customer file cust = list(confcust.get_customers())[0] jobstatedir = confcust.get_fullstatedir(globopts['InputStateSaveDir'.lower()], cust) fetchtype = confcust.get_topofetchtype()[0] state = None logger.customer = custname uidservtype = confcust.get_uidserviceendpoints() topofeed = confcust.get_topofeed() loop = uvloop.new_event_loop() asyncio.set_event_loop(loop) try: if is_feed(topofeed): res = loop.run_until_complete(fetch_data(topofeed)) group_groups, group_endpoints = parse_source_topo(res, uidservtype, fetchtype) contacts = ParseContacts(logger, res, uidservtype, is_csv=False).get_contacts() attach_contacts_topodata(logger, contacts, group_endpoints) else: try: with open(topofeed) as fp: js = json.load(fp) group_groups, group_endpoints = parse_source_topo(js, uidservtype, fetchtype) except IOError as exc: logger.error('Customer:%s : Problem opening %s - %s' % (logger.customer, topofeed, repr(exc))) loop.run_until_complete( write_state(confcust, fixed_date, True) ) webapi_opts = get_webapi_opts(cglob, confcust) numge = len(group_endpoints) numgg = len(group_groups) # send concurrently to WEB-API in coroutines if eval(globopts['GeneralPublishWebAPI'.lower()]): loop.run_until_complete( asyncio.gather( send_webapi(webapi_opts, group_groups, 'groups', fixed_date), send_webapi(webapi_opts, group_endpoints,'endpoints', fixed_date) ) ) if eval(globopts['GeneralWriteAvro'.lower()]): write_avro(confcust, group_groups, group_endpoints, fixed_date) logger.info('Customer:' + custname + ' Fetched Endpoints:%d' % (numge) + ' Groups(%s):%d' % (fetchtype, numgg)) except (ConnectorHttpError, ConnectorParseError, KeyboardInterrupt) as exc: logger.error(repr(exc)) loop.run_until_complete( write_state(confcust, fixed_date, False ) ) if __name__ == '__main__': main()

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import keras from keras.models import Sequential from keras.layers import Conv2D, MaxPooling2D from keras.datasets import cifar10 from keras.layers import Dense, Activation, Flatten, Dropout, BatchNormalization from keras.layers import Conv2D, MaxPooling2D def train_model(x_train, y_train, x_test, y_test, model_name): num_classes = 10 batch_size = 32 epochs = 25 y_train = keras.utils.to_categorical(y_train, num_classes) y_test = keras.utils.to_categorical(y_test, num_classes) model = Sequential() model.add(Conv2D(32, (3, 3), padding='same', input_shape=\ x_train.shape[1:])) model.add(Activation('relu')) model.add(Conv2D(32, (3, 3))) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Conv2D(64, (3, 3), padding='same')) model.add(Activation('relu')) model.add(Conv2D(64, (3, 3))) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(512)) model.add(Activation('relu')) model.add(Dropout(0.5)) model.add(Dense(num_classes)) model.add(Activation('softmax')) opt = keras.optimizers.rmsprop(lr=0.0001, decay=1e-06) pass x_train = x_train.astype('float32') x_test = x_test.astype('float32') x_train /= 255 x_test /= 255 model.fit(x_train, y_train, batch_size=\ batch_size, epochs=\ epochs, validation_data=\ (x_test, y_test), shuffle=\ True) model.save(model_name) scores = model.evaluate(x_test, y_test, verbose=1) return (scores[0], scores[1])

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import cv2 def drawline(img, pt1, pt2, color, thickness=1, style='dotted', gap=10): dist = ((pt1[0] - pt2[0]) ** 2 + (pt1[1] - pt2[1]) ** 2) ** .5 pts= [] for i in np.arange(0, dist, gap): r = i / dist x = int((pt1[0] * (1 - r) + pt2[0] * r) + .5) y = int((pt1[1] * (1 - r) + pt2[1] * r) + .5) p = (x, y) pts.append(p) if style == 'dotted': for p in pts: cv2.circle(img, p, thickness, color, -1) else: s = pts[0] e = pts[0] i = 0 for p in pts: s = e e = p if i % 2 == 1: cv2.line(img,s,e,color,thickness) i += 1 def drawpoly(img, pts, color, thickness=1, style='dotted'): s = pts[0] e = pts[0] pts.append(pts.pop(0)) for p in pts: s = e e = p drawline(img, s, e, color, thickness, style) def drawrect(img, pt1, pt2, color, thickness=1, style='dotted'): pts = [pt1, (pt2[0], pt1[1]), pt2, (pt1[0], pt2[1])] drawpoly(img, pts, color, thickness, style)

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from tensorflow.examples.tutorials.mnist import input_data import matplotlib.pyplot as plt import numpy as np import pickle import random from model_2 import * def unpickle(file): with open(file, 'rb') as fo: dict_ = pickle.load(fo, encoding='bytes') return dict_ def calculate(): vars = tf.trainable_variables() for var in vars: print(var) all_number=sum([np.prod(var.get_shape()) for var in vars]) print('you use %d parameters' %(all_number)) return if __name__ == '__main__': data_list=list() mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) train_img = mnist.train.images train_label = mnist.train.labels test_img = mnist.test.images test_label = mnist.test.labels index = list(range(len(train_img))) random.shuffle(index) # print(data_list[0:3]) epoch = 10 batch_size = 100 num_batch = int(55000 / 100) CNN = CNN_3() loss = CNN.loss learning_rates= [random.uniform(0.001, 0.005),random.uniform(0.00001, 0.00005),random.uniform(0.0001, 0.0005),random.uniform(0.000001, 0.000005)] for learning_rate in learning_rates: CNN.learning_rate = learning_rate Train_step = tf.train.AdamOptimizer(CNN.learning_rate).minimize(loss) loss_array = [] step = 0 step_array = [] sess = tf.Session() sess.run(tf.global_variables_initializer()) sess.run(tf.local_variables_initializer()) for i in range(epoch): random.shuffle(index) train_img = train_img[index] train_label= train_label[index] for j in range(num_batch): x_data =train_img[j*100:(j+1)*100] y_data=train_label[j*100:(j+1)*100] _=sess.run(Train_step,feed_dict={CNN.x:x_data,CNN.y:y_data}) if (j+1) % 55 == 0: loss_show=sess.run(loss,feed_dict={CNN.x:x_data,CNN.y:y_data}) print("epoch %d num_batch %2d loss = %.5f" %(i,j,loss_show)) loss_array+=[loss_show] step_array+=[step] step +=1 plt.plot(step_array,loss_array,label='learning_rate= {}'.format(learning_rate)) sess.close() plt.yscale('symlog') plt.title('CNN_3 Loss on training') plt.legend(loc='upper left') plt.style.use('ggplot') plt.savefig('three_hidden_layer_loss_step.png') plt.show()

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# pylint: disable=too-few-public-methods "A Circle Abstraction" from interface_shape import IShape class Circle(IShape): "The Circle is a Refined Abstraction" def __init__(self, implementer): self.implementer = implementer() def draw(self): self.implementer.draw_implementation()

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aaron-kr/learning-opencv

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# 0410.py import cv2 import numpy as np src = cv2.imread('../../img/spirit-week.jpg', cv2.IMREAD_GRAYSCALE) shape = src.shape[0], src.shape[1], 3 dst = np.zeros(shape, dtype = np.uint8) # dst[:,:,0] = src # B - Blue channel # dst[:,:,1] = src # G - Green channel dst[:,:,2] = src # R - Red channel dst[100:400, 200:300, :] = [255,255,255] cv2.imshow('src', src) cv2.imshow('dst', dst) cv2.waitKey() cv2.destroyAllWindows()

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import json import sys import argparse sys.path.insert(0, './src') from logger_config import logger from metrics import compute_mrr, trec_eval from utils import save_json_to_file from data_utils import load_qrels, load_msmarco_predictions parser = argparse.ArgumentParser(description='compute metrics for ms-marco predictions') parser.add_argument('--in-path', default='', type=str, metavar='N', help='path to predictions in msmarco output format') parser.add_argument('--qrels', default='./data/msmarco/dev_qrels.txt', type=str, metavar='N', help='path to qrels') args = parser.parse_args() logger.info('Args={}'.format(json.dumps(args.__dict__, ensure_ascii=False, indent=4))) def main(): qrels = load_qrels(path=args.qrels) predictions = load_msmarco_predictions(args.in_path) all_metrics = trec_eval(qrels=qrels, predictions=predictions) all_metrics['mrr'] = compute_mrr(qrels=qrels, predictions=predictions) logger.info(json.dumps(all_metrics, ensure_ascii=False, indent=4)) save_json_to_file(all_metrics, '{}.metrics.json'.format(args.in_path)) if __name__ == '__main__': main()

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def staircase(n): for i in range(1,n+1): #print the #, i times. so it will increase with each iteration print(('#'*i).rjust(n,' ')) n = int(input()) staircase(n) # str.rjust(width[, fillchar]) #Parameters # width − This is the string length in total after padding. # fillchar − This is the filler character, default is a space.

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import time from watchdog.observers import Observer from watchdog.events import FileSystemEventHandler import nibbler.trading.collectors.futures_collector as futures class MyHandler(FileSystemEventHandler): def on_modified(self, event): event_list = event.src_path.split('\\') filename = event_list[-1] print(filename) if "BTC" in filename: print('success') def runner(): event_handler = MyHandler() observer = Observer() observer.schedule(event_handler, path=r'C:\Users\James\Documents\GitHub\Nibbler\nibbler\trading\collectors', recursive=False) observer.start() try: while True: time.sleep(1) except KeyboardInterrupt: observer.stop() observer.join() runner()

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from django.conf.urls import url from . import views urlpatterns = [ url(r'^$', views.index), url(r'^new/', views.new), url(r'^create/', views.create), url(r'^(?P<number>[0-9]+)/$', views.show), url(r'^(?P<number>[0-9]+)/edit/', views.edit), url(r'^(?P<number>[0-9]+)/delete/', views.destroy), ]

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# encoding: utf-8 # (c) 2017-2022 Open Risk, all rights reserved # # TransitionMatrix is licensed under the Apache 2.0 license a copy of which is included # in the source distribution of TransitionMatrix. This is notwithstanding any licenses of # third-party software included in this distribution. You may not use this file except in # compliance with the License. # # 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. """ Example workflows using transitionMatrix to estimate an empirical transition matrix from duration type data. The datasets are produced in examples/generate_synthetic_data.py """ import matplotlib.pyplot as plt import numpy as np import pandas as pd import transitionMatrix as tm from transitionMatrix import source_path from transitionMatrix.estimators import aalen_johansen_estimator as aj from transitionMatrix.utils.converters import datetime_to_float dataset_path = source_path + "datasets/" # Example 1: Credit Rating Migration example # Example 2: Simple 2x2 Matrix for testing # Example 3: Credit Rating Migration example with timestamps in raw date format example = 3 # Step 1 # Load the data set into a pandas frame # Make sure state is read as a string and not as integer # Second synthetic data example: # n entities with ~10 observations each, [0,1] state, 50%/50% transition matrix print("> Step 1: Load the data set into a pandas frame") if example == 1: data = pd.read_csv(dataset_path + 'synthetic_data7.csv', dtype={'State': str}) elif example == 2: data = pd.read_csv(dataset_path + 'synthetic_data8.csv', dtype={'State': str}) elif example == 3: data = pd.read_csv(dataset_path + 'synthetic_data9.csv', parse_dates=True) # convert datetime data to floats, return also the observation window data bounds, data = datetime_to_float(data) print('Start and End dates', bounds) sorted_data = data.sort_values(['Time', 'ID'], ascending=[True, True]) print(sorted_data.head(5)) print(sorted_data.describe()) # Step 2 # Describe and validate the State Space against the data print("> Step 2: Describe and validate the State Space against the data") # We insert the expected labels of the state space if example == 1 or example == 3: definition = [('0', "AAA"), ('1', "AA"), ('2', "A"), ('3', "BBB"), ('4', "BB"), ('5', "B"), ('6', "CCC"), ('7', "D")] elif example == 2: definition = [('0', "G"), ('1', "B")] myState = tm.StateSpace(definition) myState.describe() # We validate that indeed the data set conforms to our expectations labels = {'State': 'From'} print(myState.validate_dataset(dataset=sorted_data, labels=labels)) labels = {'State': 'To'} print(myState.validate_dataset(dataset=sorted_data, labels=labels)) # Step 3 # Estimate matrices using the Aalen-Johansen estimator print("> Step 3: Estimate matrices using the Aalen-Johansen estimator") myEstimator = aj.AalenJohansenEstimator(states=myState) # labels = {'Timestamp': 'Time', 'From_State': 'From', 'To_State': 'To', 'ID': 'ID'} labels = {'Time': 'Time', 'From': 'From', 'To': 'To', 'ID': 'ID'} etm, times = myEstimator.fit(sorted_data, labels=labels) # Step 4 # Print the cumulative computed matrix print("> Step 4: Print the cumulative computed matrix") print(etm[:, :, -1]) # Step 5 # Create a visualization of the transition rates if example == 1 or example == 3: # Now lets plot a collection of curves for all ratings print("> Plot the transition curves") Periods = 10 Ratings = 8 m = 4 n = 2 f, axarr = plt.subplots(m, n) f.subplots_adjust(left=0.05, bottom=0.05, right=0.95, top=0.90, wspace=0.0, hspace=0.1) # plt.style.use(['ggplot']) for ri in range(0, Ratings): axj = int(ri / 2) axi = ri % 2 print(ri, axj, axi) curves = [] for rf in range(0, Ratings): cPD = etm[ri, rf, :] curves.append(cPD) # axarr[axj, axi].set_aspect(5) axarr[axj, axi].set_ylabel('State ' + str(ri), fontsize=12) axarr[axj, axi].set_xlabel("Time") axarr[axj, axi].plot(times[1:], curves[rf], label="RI=%d" % (rf,)) # axarr[axj, axi].set_xticks(range(10), minor=False) axarr[axj, axi].set_yticks(np.linspace(0, 1, 5), minor=False) # axarr[axj, axi].yaxis.grid(True, which='minor') axarr[axj, axi].margins(y=0.05, x=0.05) axarr[axj, axi].autoscale() axarr[axj, axi].grid(True) # plt.tight_layout() f.suptitle("Multi-period Transition Probabilities", fontsize=12) # plt.title("Multi-period Transition Probabilities") plt.savefig("transition_probabilities.png") plt.show() def main(): print("Done") if __name__ == "__main__": main()

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import itertools nominals = ['2','3','4','5','6','7','8','9','10','валет','дама','король','туз'] suits = ['пик','треф','бубен','червей'] allcomb = list(itertools.product(nominals,suits)) comb = [] for elem in allcomb: if (elem not in comb) and (list(elem).reverse() not in comb): comb.append(' '.join(elem)) comb.sort() three = sorted(itertools.combinations(comb, 3)) for comb in three: comb = list(comb) comb.sort() if any([x.split()[1] == 'червей' for x in comb]) and any([y.split()[0] in nominals[9:] for y in comb]): print(', '.join(list(comb)))

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import itertools x, y = input().split() for i in range(1, int(y) + 1): out = list(itertools.combinations(sorted(x), i)) for n in out: print(*n, sep='')

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"The Flyweight Use Case Example" from table import Table from flyweight_factory import FlyweightFactory TABLE = Table(3, 3) TABLE.rows[0].columns[0].data = "abra" TABLE.rows[0].columns[1].data = "112233" TABLE.rows[0].columns[2].data = "cadabra" TABLE.rows[1].columns[0].data = "racadab" TABLE.rows[1].columns[1].data = "12345" TABLE.rows[1].columns[2].data = "332211" TABLE.rows[2].columns[0].data = "cadabra" TABLE.rows[2].columns[1].data = "445566" TABLE.rows[2].columns[2].data = "aa 22 bb" TABLE.rows[0].columns[0].justify = 1 TABLE.rows[1].columns[0].justify = 1 TABLE.rows[2].columns[0].justify = 1 TABLE.rows[0].columns[2].justify = 2 TABLE.rows[1].columns[2].justify = 2 TABLE.rows[2].columns[2].justify = 2 TABLE.rows[0].columns[1].width = 15 TABLE.rows[1].columns[1].width = 15 TABLE.rows[2].columns[1].width = 15 TABLE.draw() print(f"FlyweightFactory has {FlyweightFactory.get_count()} flyweights")

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import tkinter import mover import config class SmallPlane(mover.BaseMover): ''' 移动的敌机 - 大飞机 ''' def __init__(self, root, canvas, position, x, y, tags): super().__init__(root, canvas, position, x, y, tags, config.image_smallplane_width, config.image_smallplane_height, True) # 移动者的移动步长 self.steps = [config.step_length_smallplane_x, config.step_length_smallplane_y] # 移动方向 - 向下 self.move_direction = [0, 1] # 移动者加载背景图像 self.bg_image_fullname = config.images_path + config.filename_smallplane + config.filename_suffix self.bg_image = tkinter.PhotoImage(file=self.bg_image_fullname) # # 重置生命值 # super().set_lives_num(config.lives_num_enemy) def exec_move(self): if self.nw[1] < config.window_boundary_row: # Y轴边界之内正常移动 x = self.steps[0] * self.move_direction[0] y = self.steps[1] * self.move_direction[1] self.base_move(self.bg_image_tags, x, y) else: # Y轴边界之外错误处理 self.base_move(self.bg_image_tags, 0, -config.window_boundary_row) # 获取死亡图片 def get_dead_images(self): img = [] if self.do_dead_play: for i in self.dead_image_index: image_fullname = config.images_path + config.filename_smallplane + str(i) + config.filename_suffix image = tkinter.PhotoImage(file=self.bg_image_fullname) img.append(image) return img

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import warnings from pandas.compat import lrange import numpy as np from pandas.core.dtypes.common import _ensure_platform_int from pandas.core.frame import DataFrame import pandas.core.algorithms as algorithms def pivot_annual(series, freq=None): """ Deprecated. Use ``pivot_table`` instead. Group a series by years, taking leap years into account. The output has as many rows as distinct years in the original series, and as many columns as the length of a leap year in the units corresponding to the original frequency (366 for daily frequency, 366*24 for hourly...). The fist column of the output corresponds to Jan. 1st, 00:00:00, while the last column corresponds to Dec, 31st, 23:59:59. Entries corresponding to Feb. 29th are masked for non-leap years. For example, if the initial series has a daily frequency, the 59th column of the output always corresponds to Feb. 28th, the 61st column to Mar. 1st, and the 60th column is masked for non-leap years. With a hourly initial frequency, the (59*24)th column of the output always correspond to Feb. 28th 23:00, the (61*24)th column to Mar. 1st, 00:00, and the 24 columns between (59*24) and (61*24) are masked. If the original frequency is less than daily, the output is equivalent to ``series.convert('A', func=None)``. Parameters ---------- series : Series freq : string or None, default None Returns ------- annual : DataFrame """ msg = "pivot_annual is deprecated. Use pivot_table instead" warnings.warn(msg, FutureWarning) index = series.index year = index.year years = algorithms.unique1d(year) if freq is not None: freq = freq.upper() else: freq = series.index.freq if freq == 'D': width = 366 offset = np.asarray(index.dayofyear) - 1 # adjust for leap year offset[(~isleapyear(year)) & (offset >= 59)] += 1 columns = lrange(1, 367) # todo: strings like 1/1, 1/25, etc.? elif freq in ('M', 'BM'): width = 12 offset = np.asarray(index.month) - 1 columns = lrange(1, 13) elif freq == 'H': width = 8784 grouped = series.groupby(series.index.year) defaulted = grouped.apply(lambda x: x.reset_index(drop=True)) defaulted.index = defaulted.index.droplevel(0) offset = np.asarray(defaulted.index) offset[~isleapyear(year) & (offset >= 1416)] += 24 columns = lrange(1, 8785) else: raise NotImplementedError(freq) flat_index = (year - years.min()) * width + offset flat_index = _ensure_platform_int(flat_index) values = np.empty((len(years), width)) values.fill(np.nan) values.put(flat_index, series.values) return DataFrame(values, index=years, columns=columns) def isleapyear(year): """ Returns true if year is a leap year. Parameters ---------- year : integer / sequence A given (list of) year(s). """ msg = "isleapyear is deprecated. Use .is_leap_year property instead" warnings.warn(msg, FutureWarning) year = np.asarray(year) return np.logical_or(year % 400 == 0, np.logical_and(year % 4 == 0, year % 100 > 0))

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n = int(input()) a = list(map(int,input().split())) if 1 not in a: print(-1) exit() x = 1 cnt = 0 for i in range(n): if a[i] == x: x += 1 else: cnt += 1 print(cnt)

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# Generated by Django 3.1.1 on 2021-06-24 06:56 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('Product', '0011_auto_20210623_1817'), ] operations = [ migrations.CreateModel( name='Order', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created', models.DateTimeField(auto_now_add=True)), ('is_paid', models.BooleanField(default=False)), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='OrderItem', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('quantity', models.PositiveIntegerField()), ('order', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='order_item', to='Order.order')), ('product', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='Product.product')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

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class Solution: def findNthDigit(self, n: int) -> int: length, start, count = 1, 1, 9 while n > length * count: n -= length * count length += 1 count *= 10 start *= 10 start += (n - 1) // length return int(str(start)[(n - 1) % length]) res = Solution().findNthDigit(15) print(res)

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# Generated by Django 3.2 on 2021-05-22 03:32 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('store', '0001_initial'), ('carts', '0001_initial'), ] operations = [ migrations.AddField( model_name='cartitem', name='product', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='store.product'), ), migrations.AddField( model_name='cartitem', name='variations', field=models.ManyToManyField(blank=True, to='store.Variation'), ), ]

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#!/usr/bin/env python3 """ Комплексные условия в if (and, or) """ if True and True and False: print("NOPE") if not True or False: print("NOPE") if None or None or 1: print("yeeep")

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from django.db import models from django.utils.encoding import python_2_unicode_compatible class Event(models.Model): # Oracle can have problems with a column named "date" date = models.DateField(db_column="event_date") class Parent(models.Model): name = models.CharField(max_length=128) class Child(models.Model): parent = models.ForeignKey(Parent, editable=False, null=True) name = models.CharField(max_length=30, blank=True) age = models.IntegerField(null=True, blank=True) class Genre(models.Model): name = models.CharField(max_length=20) class Band(models.Model): name = models.CharField(max_length=20) nr_of_members = models.PositiveIntegerField() genres = models.ManyToManyField(Genre) @python_2_unicode_compatible class Musician(models.Model): name = models.CharField(max_length=30) def __str__(self): return self.name @python_2_unicode_compatible class Group(models.Model): name = models.CharField(max_length=30) members = models.ManyToManyField(Musician, through='Membership') def __str__(self): return self.name class Membership(models.Model): music = models.ForeignKey(Musician) group = models.ForeignKey(Group) role = models.CharField(max_length=15) class Quartet(Group): pass class ChordsMusician(Musician): pass class ChordsBand(models.Model): name = models.CharField(max_length=30) members = models.ManyToManyField(ChordsMusician, through='Invitation') class Invitation(models.Model): player = models.ForeignKey(ChordsMusician) band = models.ForeignKey(ChordsBand) instrument = models.CharField(max_length=15) class Swallow(models.Model): origin = models.CharField(max_length=255) load = models.FloatField() speed = models.FloatField() class Meta: ordering = ('speed', 'load') class SwallowOneToOne(models.Model): swallow = models.OneToOneField(Swallow) class UnorderedObject(models.Model): """ Model without any defined `Meta.ordering`. Refs #17198. """ bool = models.BooleanField(default=True) class OrderedObjectManager(models.Manager): def get_queryset(self): return super(OrderedObjectManager, self).get_queryset().order_by('number') class OrderedObject(models.Model): """ Model with Manager that defines a default order. Refs #17198. """ name = models.CharField(max_length=255) bool = models.BooleanField(default=True) number = models.IntegerField(default=0, db_column='number_val') objects = OrderedObjectManager() class CustomIdUser(models.Model): uuid = models.AutoField(primary_key=True)

[ "multics_luo@163.com" ]

multics_luo@163.com

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/Exps_7_v3/doc3d/Ablation4_ch016_ep010/I_w_M_to_W_pyr/pyr_0s/L7/step10_a.py

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[]

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KongBOy/kong_model2

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1af20b168ffccf0d5293a393a40a9fa9519410b2

refs/heads/master

2022-10-14T03:09:22.543998

2022-10-06T11:33:42

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############################################################################################################################################################################################################# ############################################################################################################################################################################################################# ### 把 kong_model2 加入 sys.path import os code_exe_path = os.path.realpath(__file__) ### 目前執行 step10_b.py 的 path code_exe_path_element = code_exe_path.split("\\") ### 把 path 切分等等要找出 kong_model 在第幾層 code_dir = "\\".join(code_exe_path_element[:-1]) kong_layer = code_exe_path_element.index("kong_model2") ### 找出 kong_model2 在第幾層 kong_model2_dir = "\\".join(code_exe_path_element[:kong_layer + 1]) ### 定位出 kong_model2 的 dir import sys ### 把 kong_model2 加入 sys.path sys.path.append(kong_model2_dir) sys.path.append(code_dir) # print(__file__.split("\\")[-1]) # print(" code_exe_path:", code_exe_path) # print(" code_exe_path_element:", code_exe_path_element) # print(" code_dir:", code_dir) # print(" kong_layer:", kong_layer) # print(" kong_model2_dir:", kong_model2_dir) ############################################################################################################################################################################################################# kong_to_py_layer = len(code_exe_path_element) - 1 - kong_layer ### 中間 -1 是為了長度轉index # print(" kong_to_py_layer:", kong_to_py_layer) if (kong_to_py_layer == 0): template_dir = "" elif(kong_to_py_layer == 2): template_dir = code_exe_path_element[kong_layer + 1][0:] ### [7:] 是為了去掉 step1x_，後來覺得好像改有意義的名字不去掉也行所以改 0 elif(kong_to_py_layer == 3): template_dir = code_exe_path_element[kong_layer + 1][0:] + "/" + code_exe_path_element[kong_layer + 2][0:] ### [5:] 是為了去掉 mask_ ，前面的 mask_ 是為了python 的 module 不能數字開頭，隨便加的這樣子，後來覺得自動排的順序也可以接受，所以改0 elif(kong_to_py_layer > 3): template_dir = code_exe_path_element[kong_layer + 1][0:] + "/" + code_exe_path_element[kong_layer + 2][0:] + "/" + "/".join(code_exe_path_element[kong_layer + 3: -1]) # print(" template_dir:", template_dir) ### 舉例： template_dir: 7_mask_unet/5_os_book_and_paper_have_dtd_hdr_mix_bg_tv_s04_mae ############################################################################################################################################################################################################# exp_dir = template_dir ############################################################################################################################################################################################################# from step06_a_datas_obj import * from step09_0side_L7 import * from step10_a2_loss_info_obj import * from step10_b2_exp_builder import Exp_builder rm_paths = [path for path in sys.path if code_dir in path] for rm_path in rm_paths: sys.path.remove(rm_path) rm_moduless = [module for module in sys.modules if "step09" in module] for rm_module in rm_moduless: del sys.modules[rm_module] ############################################################################################################################################################################################################# ''' exp_dir 是決定 result_dir 的 "上一層"資料夾名字喔！ exp_dir要巢狀也沒問題～比如：exp_dir = "6_mask_unet/自己命的名字"，那 result_dir 就都在： 6_mask_unet/自己命的名字/result_a 6_mask_unet/自己命的名字/result_b 6_mask_unet/自己命的名字/... ''' use_db_obj = type8_blender_kong_doc3d_in_I_gt_W_ch_norm_v2 use_loss_obj = [mae_s001_sobel_k9_s001_loss_info_builder.set_loss_target("UNet_W").copy()] ### z, y, x 順序是看 step07_b_0b_Multi_UNet 來對應的喔 ############################################################# ### 為了resul_analyze畫空白的圖，建一個empty的 Exp_builder empty = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_0side, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_0side.kong_model.model_describe) .set_train_args(epochs= 10) .set_train_iter_args(it_see_fq=900 * 5, it_save_fq=900 * 5, it_down_step="half", it_down_fq=900).set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="為了resul_analyze畫空白的圖，建一個empty的 Exp_builder") ############################################################# ch032_0side = Exp_builder().set_basic("train", use_db_obj, ch032_pyramid_0side, use_loss_obj, exp_dir=exp_dir, code_exe_path=code_exe_path, describe_end=ch032_pyramid_0side.kong_model.model_describe) .set_train_args(epochs= 10) .set_train_iter_args(it_see_fq=900 * 5, it_save_fq=900 * 5, it_down_step="half", it_down_fq=900).set_train_in_gt_use_range(use_in_range=Range(0, 1), use_gt_range=Range(0, 1)).set_result_name(result_name="") ############################################################# if(__name__ == "__main__"): print("build exps cost time:", time.time() - start_time) if len(sys.argv) < 2: ############################################################################################################ ### 直接按 F5 或打 python step10_b1_exp_obj_load_and_train_and_test.py，後面沒有接東西喔！才不會跑到下面給 step10_b_subprocss.py 用的程式碼~~~ ch032_0side.build().run() # print('no argument') sys.exit() ### 以下是給 step10_b_subprocess.py 用的，相當於cmd打 python step10_b1_exp_obj_load_and_train_and_test.py 某個exp.build().run() eval(sys.argv[1])

[ "s89334roy@yahoo.com.tw" ]

s89334roy@yahoo.com.tw

1b5f7970359cd50efcaeb24cab8c592711e3bd4d

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/test/test_forecaster_entrypoints.py

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[ "Apache-2.0" ]

permissive

canerturkmen/gluon-ts

2f2d46f9b01f5ee07a51a11e822b1c72c2475caa

57ae07f571ff123eac04af077870c1f216f99d5c

refs/heads/master

2022-09-10T23:30:26.162245

2022-04-20T12:44:01

192,873,578

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2

Apache-2.0

2020-08-04T16:58:48

2019-06-20T07:43:07

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UTF-8

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py

# Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). # You may not use this file except in compliance with the License. # A copy of the License is located at # # http://www.apache.org/licenses/LICENSE-2.0 # # or in the "license" file accompanying this file. This file is distributed # on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either # express or implied. See the License for the specific language governing # permissions and limitations under the License. import pkg_resources # def test_forecaster_entrypoints(): # for entry_point in pkg_resources.iter_entry_points("gluonts_forecasters"): # entry_point.load()

[ "noreply@github.com" ]

canerturkmen.noreply@github.com

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/generated_tempdir_2019_09_15_163300/generated_part003381.py

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[]

no_license

Upabjojr/rubi_generated

76e43cbafe70b4e1516fb761cabd9e5257691374

cd35e9e51722b04fb159ada3d5811d62a423e429

refs/heads/master

2020-07-25T17:26:19.227918

2019-09-15T15:41:48

208,357,412

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from sympy.abc import * from matchpy.matching.many_to_one import CommutativeMatcher from matchpy import * from matchpy.utils import VariableWithCount from collections import deque from multiset import Multiset from sympy.integrals.rubi.constraints import * from sympy.integrals.rubi.utility_function import * from sympy.integrals.rubi.rules.miscellaneous_integration import * from sympy import * class CommutativeMatcher37234(CommutativeMatcher): _instance = None patterns = { 0: (0, Multiset({0: 1}), [ (VariableWithCount('i2.2.1.2.2.2.1.0', 1, 1, S(1)), Mul) ]) } subjects = {} subjects_by_id = {} bipartite = BipartiteGraph() associative = Mul max_optional_count = 1 anonymous_patterns = set() def __init__(self): self.add_subject(None) @staticmethod def get(): if CommutativeMatcher37234._instance is None: CommutativeMatcher37234._instance = CommutativeMatcher37234() return CommutativeMatcher37234._instance @staticmethod def get_match_iter(subject): subjects = deque([subject]) if subject is not None else deque() subst0 = Substitution() # State 37233 if len(subjects) >= 1 and isinstance(subjects[0], Pow): tmp1 = subjects.popleft() subjects2 = deque(tmp1._args) # State 37235 if len(subjects2) >= 1: tmp3 = subjects2.popleft() subst1 = Substitution(subst0) try: subst1.try_add_variable('i2.2.1.1', tmp3) except ValueError: pass else: pass # State 37236 if len(subjects2) >= 1: tmp5 = subjects2.popleft() subst2 = Substitution(subst1) try: subst2.try_add_variable('i2.2.1.2', tmp5) except ValueError: pass else: pass # State 37237 if len(subjects2) == 0: pass # State 37238 if len(subjects) == 0: pass # 0: x**j yield 0, subst2 subjects2.appendleft(tmp5) subjects2.appendleft(tmp3) subjects.appendleft(tmp1) return yield from collections import deque

[ "franz.bonazzi@gmail.com" ]

franz.bonazzi@gmail.com

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/mkt/constants/__init__.py

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[]

no_license

potch/zamboni

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refs/heads/master

2021-01-15T21:15:25.102909

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2013-01-02T20:16:10

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from .platforms import DEVICE_LOOKUP, FREE_PLATFORMS, PAID_PLATFORMS from .submit import (APP_IMAGE_SIZES, APP_PREVIEW_MINIMUMS, APP_PREVIEW_SIZES, MAX_PACKAGED_APP_SIZE)

[ "me@mattbasta.com" ]

me@mattbasta.com

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/code/venv/lib/python3.6/site-packages/passlib/utils/_blowfish/__init__.py

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[ "MIT" ]

permissive

jhkuang11/UniTrade

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refs/heads/master

2022-12-12T15:58:30.013516

2019-02-01T21:07:15

166,479,655

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MIT

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2019-01-18T22:19:45

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py

"""passlib.utils._blowfish - pure-python eks-blowfish implementation for bcrypt This is a pure-python implementation of the EKS-Blowfish algorithm described by Provos and Mazieres in `A Future-Adaptable Password Scheme <http://www.openbsd.org/papers/bcrypt-paper.ps>`_. This package contains two submodules: * ``_blowfish/base.py`` contains a class implementing the eks-blowfish algorithm using easy-to-examine code. * ``_blowfish/unrolled.py`` contains a subclass which replaces some methods of the original class with sped-up versions, mainly using unrolled loops and local variables. this is the class which is actually used by Passlib to perform BCrypt in pure python. This module is auto-generated by a script, ``_blowfish/_gen_files.py``. Status ------ This implementation is usuable, but is an order of magnitude too slow to be usuable with real security. For "ok" security, BCrypt hashes should have at least 2**11 rounds (as of 2011). Assuming a desired response time <= 100ms, this means a BCrypt implementation should get at least 20 rounds/ms in order to be both usuable *and* secure. On a 2 ghz cpu, this implementation gets roughly 0.09 rounds/ms under CPython (220x too slow), and 1.9 rounds/ms under PyPy (10x too slow). History ------- While subsequently modified considerly for Passlib, this code was originally based on `jBcrypt 0.2 <http://www.mindrot.org/projects/jBCrypt/>`_, which was released under the BSD license:: Copyright (c) 2006 Damien Miller <djm@mindrot.org> Permission to use, copy, modify, and distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. """ #============================================================================= # imports #============================================================================= # core from itertools import chain import struct # pkg from passlib.utils import bcrypt64, getrandbytes, rng from passlib.utils.compat import b, bytes, BytesIO, unicode, u from passlib.utils._blowfish.unrolled import BlowfishEngine # local __all__ = [ 'BlowfishEngine', 'raw_bcrypt', ] #============================================================================= # bcrypt constants #============================================================================= # bcrypt constant data "OrpheanBeholderScryDoubt" as 6 integers BCRYPT_CDATA = [ 0x4f727068, 0x65616e42, 0x65686f6c, 0x64657253, 0x63727944, 0x6f756274 ] # struct used to encode ciphertext as digest (last output byte discarded) digest_struct = struct.Struct(">6I") #============================================================================= # base bcrypt helper # # interface designed only for use by passlib.handlers.bcrypt:BCrypt # probably not suitable for other purposes #============================================================================= BNULL = b('\x00') def raw_bcrypt(password, ident, salt, log_rounds): """perform central password hashing step in bcrypt scheme. :param password: the password to hash :param ident: identifier w/ minor version (e.g. 2, 2a) :param salt: the binary salt to use (encoded in bcrypt-base64) :param rounds: the log2 of the number of rounds (as int) :returns: bcrypt-base64 encoded checksum """ #=================================================================== # parse inputs #=================================================================== # parse ident assert isinstance(ident, unicode) if ident == u('2'): minor = 0 elif ident == u('2a'): minor = 1 # XXX: how to indicate caller wants to use crypt_blowfish's # workaround variant of 2a? elif ident == u('2x'): raise ValueError("crypt_blowfish's buggy '2x' hashes are not " "currently supported") elif ident == u('2y'): # crypt_blowfish compatibility ident which guarantees compat w/ 2a minor = 1 else: raise ValueError("unknown ident: %r" % (ident,)) # decode & validate salt assert isinstance(salt, bytes) salt = bcrypt64.decode_bytes(salt) if len(salt) < 16: raise ValueError("Missing salt bytes") elif len(salt) > 16: salt = salt[:16] # prepare password assert isinstance(password, bytes) if minor > 0: password += BNULL # validate rounds if log_rounds < 4 or log_rounds > 31: raise ValueError("Bad number of rounds") #=================================================================== # # run EKS-Blowfish algorithm # # This uses the "enhanced key schedule" step described by # Provos and Mazieres in "A Future-Adaptable Password Scheme" # http://www.openbsd.org/papers/bcrypt-paper.ps # #=================================================================== engine = BlowfishEngine() # convert password & salt into list of 18 32-bit integers (72 bytes total). pass_words = engine.key_to_words(password) salt_words = engine.key_to_words(salt) # truncate salt_words to original 16 byte salt, or loop won't wrap # correctly when passed to .eks_salted_expand() salt_words16 = salt_words[:4] # do EKS key schedule setup engine.eks_salted_expand(pass_words, salt_words16) # apply password & salt keys to key schedule a bunch more times. rounds = 1<<log_rounds engine.eks_repeated_expand(pass_words, salt_words, rounds) # encipher constant data, and encode to bytes as digest. data = list(BCRYPT_CDATA) i = 0 while i < 6: data[i], data[i+1] = engine.repeat_encipher(data[i], data[i+1], 64) i += 2 raw = digest_struct.pack(*data)[:-1] return bcrypt64.encode_bytes(raw) #============================================================================= # eof #=============================================================================

[ "jhkuang11@gmail.com" ]

jhkuang11@gmail.com

816522a328e2247a1e43e6f0537dd652c8266d33

6a2c2af113bb8b4d55db6ceabc6e78a0bbcd1f91

/genus processing/Double Breasted.py

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[]

no_license

JinghongM/Everlasting_Data_Cleansing

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237073980b2bd1697db578013c7463dcbc1492fb

refs/heads/master

2021-04-26T23:48:38.083155

2018-06-21T20:00:11

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import pandas as pd import copy import os.path Pattern=6 Material=7 Species=4 CGP = pd.read_excel("../Realdata.xlsx") for row in range(1,CGP.shape[0]): genus = str(CGP.iat[row,3]) if "Double Breasted" in genus: print(row) CGP.iat[row,3] = genus.replace("Double Breasted ","") CGP.iat[row,Species] = "Double Breasted" i=0 #process headers while i<len(CGP.columns.values): if "Unnamed" in CGP.columns.values[i]: CGP.columns.values[i] = '' i+=1 CGP.to_excel('../Realdata.xlsx',index=False)

[ "noreply@github.com" ]

JinghongM.noreply@github.com

5e7fd79ebbe73607afa51ba6a52d8e1ee3a6c9b5

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/Client/config/Client_config_info.py

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[]

no_license

YangQian1992/FTP

932f32d5ed934bae295bd674757f7af23d0ad1ba

87d3a78522e7eb8058def1d74d7f32f0f61f1b86

refs/heads/master

2020-03-31T16:28:35.146329

2018-10-10T06:53:12

152,376,641

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null

UTF-8

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136

py

personal_config_info = { 'SERVER_IP':'127.0.0.1', 'SERVER_PORT':8082, 'CODING':'utf-8',#编码方式 'BLOCK_SIZE':1024 }

[ "1289089651@qq.com" ]

1289089651@qq.com

0c4aa77a3094093376053b5f19d0e964a4b1427a

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/12/12.1/Path_test1.py

3093e21b3c397c3f1a090b05e991c3d7de8b5f0f

[]

no_license

zhyErick/fengkuang_python

b0f0c78273420fd862691799bfd7e4f1b6eadf80

6d50ad3b7d4ae05d06379c2dc87d91081964ec6d

refs/heads/master

2021-02-14T08:23:26.616211

2020-05-06T13:08:07

244,788,500

0

null

UTF-8

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463

py

from pathlib import * # 获取当前目录 p = Path('../') # 遍历当前目录下的所有文件和子目录 for x in p.iterdir(): print(x) # 获取上一级目录 p = Path('../') # 获取上级目录及其所有子目录的.py文件 for x in p.glob('**/*.py'): print(x) # 获取C:\python\oldboy_python对应的目录 p = Path('C:\python\oldboy_python') # 获取当前目录及其所有子目录下的.py文件 for x in p.glob('*/*.py'): print(x)

[ "xingzhishangyang@163.com" ]

xingzhishangyang@163.com

16333d2fe48ad23cc47270a1b8fc53973efafdf3

90dc57404ea2e98006adba91f53ea9cc92124bb4

/spare_parts/forms.py

a6679136c699e7b1b3cdd28e55c4d7b38fcc7460

[]

no_license

AndreySkryl/flask-test

e57409c779f113980a9acf1c6f9a37be5106e119

8979e15789160e65a7ef6123e3ba638e764d8131

refs/heads/main

2023-04-24T18:33:59.675028

2021-05-10T15:16:56

365,334,649

1

0

null

UTF-8

Python

false

281

py

from wtforms import Form, StringField, TextAreaField, IntegerField class SparePartForm(Form): title = StringField('Заголовок') price = IntegerField('Цена') amount = IntegerField('Количество') description = TextAreaField('Описание')

[ "ya.skryl@yandex.ru" ]

ya.skryl@yandex.ru

f1cd67923e90294c3a5c457d1925664b58b06270

e23a4f57ce5474d468258e5e63b9e23fb6011188

/125_algorithms/_exercises/exercises/Python_Hand-on_Solve_200_Problems/Section 7 Dictionary/check_key_exist_solution.py

637344c193288ad01e3c9e4394cbd7653b485f05

[]

no_license

syurskyi/Python_Topics

52851ecce000cb751a3b986408efe32f0b4c0835

be331826b490b73f0a176e6abed86ef68ff2dd2b

refs/heads/master

2023-06-08T19:29:16.214395

2023-05-29T17:09:11

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3

2

null

2023-02-16T03:08:10

2019-11-09T02:58:47

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UTF-8

Python

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py

# # To add a new cell, type '# %%' # # To add a new markdown cell, type '# %% [markdown]' # # %% # # --------------------------------------------------------------- # # python best courses https://courses.tanpham.org/ # # --------------------------------------------------------------- # # Check if a given key already exists in a dictionary # # input # # d = {1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60} # # is_key_present(5) # # is_key_present(9) # # output # # Key is present in the dictionary # # Key is not present in the dictionary # # d _ {1: 10, 2: 20, 3: 30, 4: 40, 5: 50, 6: 60} # ___ is_key_present x # __ ? __ ? # print('Key is present in the dictionary') # ____ # print('Key is not present in the dictionary') # ? 5 # ? 9 # #

[ "sergejyurskyj@yahoo.com" ]

sergejyurskyj@yahoo.com

b0dad98cc918993b31888c8234bf8e6d804cb304

40eb94673bb2e015c1640665a639c508279e3df4

/cursos/_flask/flask/ejemplos/u29/aplicacion/models.py

defde3e73d247258609be8cc99c0eaf13f0671aa

[]

no_license

josedom24/plataforma_pledin

3ab5c59abd87c90f066ba9164d6d0cbc02ea816f

e0521eb103013e0f8d9e2b2ea50e6acac0d09784

refs/heads/master

2023-07-20T15:43:30.796223

2023-07-17T19:07:51

138,278,487

2

0

null

2023-05-01T20:05:34

2018-06-22T08:44:58

Python

UTF-8

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false

2,007

py

from sqlalchemy import Boolean, Column , ForeignKey from sqlalchemy import DateTime, Integer, String, Text, Float from sqlalchemy.orm import relationship from aplicacion.app import db from werkzeug.security import generate_password_hash, check_password_hash class Categorias(db.Model): """Categorías de los artículos""" __tablename__ = 'categorias' id = Column(Integer, primary_key=True) nombre = Column(String(100)) articulos = relationship("Articulos", cascade="all, delete-orphan", backref="Categorias",lazy='dynamic') def __repr__(self): return (u'<{self.__class__.__name__}: {self.id}>'.format(self=self)) class Articulos(db.Model): """Artículos de nuestra tienda""" __tablename__ = 'articulos' id = Column(Integer, primary_key=True) nombre = Column(String(100),nullable=False) precio = Column(Float,default=0) iva = Column(Integer,default=21) descripcion = Column(String(255)) image = Column(String(255)) stock = Column(Integer,default=0) CategoriaId=Column(Integer,ForeignKey('categorias.id'), nullable=False) categoria = relationship("Categorias", backref="Articulos") def precio_final(self): return self.precio+(self.precio*self.iva/100) def __repr__(self): return (u'<{self.__class__.__name__}: {self.id}>'.format(self=self)) class Usuarios(db.Model): """Usuarios""" __tablename__ = 'usuarios' id = Column(Integer, primary_key=True) username = Column(String(100),nullable=False) password_hash = Column(String(128),nullable=False) nombre = Column(String(200),nullable=False) email = Column(String(200),nullable=False) admin = Column(Boolean, default=False) def __repr__(self): return (u'<{self.__class__.__name__}: {self.id}>'.format(self=self)) @property def password(self): raise AttributeError('password is not a readable attribute') @password.setter def password(self, password): self.password_hash = generate_password_hash(password) def verify_password(self, password): return check_password_hash(self.password_hash, password)

[ "josedom24@gmail.com" ]

josedom24@gmail.com

10da254f4b916fe94485339bbb590bc46404c718

46e271e27afe50b8b62be0651d78164490911bb3

/ws_moveit/src/example/example_pkg/scripts/red.py

1ec501210d7051649bb4e99b72defa0eede3bac3

[]

no_license

Nidhiks2000/Vargi-bot

8a43af1e470b6fc84d468003f67471a1e1f47aad

3e2e7be310ed7372cb6960eea8faabec75d9fbcf

refs/heads/master

2023-07-24T01:05:10.049800

2021-09-08T16:31:08

403,935,308

0

null

UTF-8

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2,639

py

#!/usr/bin/env python import rospy import cv2 import sys from std_msgs.msg import String from sensor_msgs.msg import Image from cv_bridge import CvBridge, CvBridgeError import numpy as np class Camera1: def __init__(self): self.bridge = CvBridge() self.image_sub = rospy.Subscriber("/eyrc/vb/camera_1/image_raw", Image,self.callback) def callback(self,data): try: cv_image = self.bridge.imgmsg_to_cv2(data, "bgr8") except CvBridgeError as e: rospy.logerr(e) (rows,cols,channels) = cv_image.shape image = cv_image # Resize a 720x1280 image to 360x640 to fit it on the screen resized_image = cv2.resize(image, (720/2, 1280/2)) green = np.uint8([[[0, 255, 0]]]) #green color hsvGreen = cv2.cvtColor(green, cv2.COLOR_BGR2HSV) #hsv value of green color lowerLimit = hsvGreen[0][0][0] - 10, 100, 100 # range of green color lower limit and upper limit upperLimit = hsvGreen[0][0][0] + 10, 255, 255 red = np.uint8([[[0, 0, 255]]]) #red color hsvred = cv2.cvtColor(red, cv2.COLOR_BGR2HSV) #hsv value of red color lower = hsvred[0][0][0] - 10, 100, 100 # range of red color lower limit and upper limit upper = hsvred[0][0][0] + 10, 255, 255 hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) #convert the image into hsv lg = np.array(lowerLimit) #range of green color ug = np.array(upperLimit) green_mask = cv2.inRange(hsv, lg, ug) #green masked image cv2.imshow('green_packages', green_mask) #show the image lr = np.array(lower) #range of red color ur = np.array(upper) red_mask = cv2.inRange(hsv, lr, ur) #red masked image cv2.imshow('red_packages', red_mask) #show the image original = image.copy() image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) lower = np.array([22, 93, 0], dtype="uint8") #yellow colour lower range and upper range upper = np.array([45, 255, 255], dtype="uint8") mask = cv2.inRange(image, lower, upper) cnts = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) cnts = cnts[0] if len(cnts) == 2 else cnts[1] for c in cnts: x,y,w,h = cv2.boundingRect(c) cv2.rectangle(original, (x, y), (x + w, y + h), (36,255,12), 2) cv2.imshow('yellow_packages', mask) cv2.imshow("/eyrc/vb/camera_1/image_raw", resized_image) cv2.waitKey(3) def main(args): rospy.init_node('node_eg1_read_camera', anonymous=True) ic = Camera1() try: rospy.spin() except KeyboardInterrupt: rospy.loginfo("Shutting down") cv2.destroyAllWindows() if __name__ == '__main__': main(sys.argv)

[ "Happysunshine.disroot.org" ]

Happysunshine.disroot.org