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

411d1b5d5d006f9c41b1c82bed003b39f7fba6ac

27acd9eeb0d2b9b6326cc0477e7dbb84341e265c

/test/vraag4/src/isbn/222.py

fd40dde79d0542bab2d8bd49e8cc487684633488

[]

no_license

VerstraeteBert/algos-ds

e0fe35bc3c5b7d8276c07250f56d3719ecc617de

d9215f11cdfa1a12a3b19ade3b95fa73848a636c

refs/heads/master

2021-07-15T13:46:58.790446

2021-02-28T23:28:36

240,883,220

1

null

UTF-8

Python

false

1,127

py

def isISBN_13(code): if len(code) != 13: return False if code[:3] != "978" and code[:3] != "979": return False even = code[::2] oneven = code[1::2] even_som = 0 oneven_som = 0 for i in range(6): cijfer = int(even[i]) even_som += cijfer cijfer = int(oneven[i]) oneven_som += cijfer controle = (10 - (even_som + 3 * oneven_som) % 10) % 10 return controle == int(even[6]) def overzicht(codes): types = ["Engelstalige landen", "Franstalige landen", "Duitstalige landen", "Japan", "Russischtalige landen", "China", "Overige landen", "Fouten"] lijst = {} for soort in types: lijst[soort] = 0 for code in codes: if not isISBN_13(code): lijst["Fouten"] += 1 else: nr = code[3] if nr == "0": nr = "1" elif nr in "689": nr = "7" elif nr == "7": nr = "6" soort = types[int(nr) - 1] lijst[soort] += 1 for el in lijst: print("{}: {}".format(el, lijst[el]))

[ "bertverstraete22@gmail.com" ]

bertverstraete22@gmail.com

68166f1c54bc0727d4ea84555b656e8b4fc72753

a5200ba8b1d2b248c7c7bef5704c7e375efc1c2a

/exp_configs.py

c09ecd223c6f468e105e0d7348bd4b1cfa3bf410

[]

no_license

hongyunnchen/sps

e0c958dadca2a60b0e8d797d8e786f88669cf5c7

4ddb3567f9a1893685ea161e2b1d7ba3cb3a1fe3

refs/heads/master

2023-02-26T06:36:41.462069

2021-02-09T12:22:09

null

0

null

UTF-8

Python

false

5,448

py

from haven import haven_utils as hu import itertools # datasets kernel_datasets = ["mushrooms", # "w8a", "ijcnn", # "rcv1" ] # define runs run_list = [0] # define optimizers c_list = [0.2] sps_list = [] for c, adapt_flag in itertools.product(c_list, ['smooth_iter']): sps_list += [{'name':"sps", "c":c, 'adapt_flag':adapt_flag}] opt_list = sps_list + [{'name': 'adam'}] EXP_GROUPS = {} # define interpolation exp groups EXP_GROUPS['kernel'] = hu.cartesian_exp_group({"dataset":kernel_datasets, "model":["linear"], "loss_func": ['logistic_loss'], "acc_func": ["logistic_accuracy"], "opt": opt_list , "batch_size":[100], "max_epoch":[35], "runs":run_list}) EXP_GROUPS['mf'] = hu.cartesian_exp_group({"dataset":["matrix_fac"], "model":["matrix_fac_1", "matrix_fac_4", "matrix_fac_10", "linear_fac"], "loss_func": ["squared_loss"], "opt": opt_list, "acc_func":["mse"], "batch_size":[100], "max_epoch":[50], "runs":run_list}) EXP_GROUPS['mnist'] = hu.cartesian_exp_group({"dataset":["mnist"], "model":["mlp"], "loss_func": ["softmax_loss"], "opt":[{'name':"sps", "c":c, 'adapt_flag':'smooth_iter', 'centralize_grad':True}] + opt_list, "acc_func":["softmax_accuracy"], "batch_size":[128], "max_epoch":[200], "runs":run_list}) EXP_GROUPS['deep'] = (hu.cartesian_exp_group({"dataset":["cifar10"], "model":["resnet34", "densenet121"], "loss_func": ["softmax_loss"], "opt": opt_list, "acc_func":["softmax_accuracy"], "batch_size":[128], "max_epoch":[200], "runs":run_list}) + hu.cartesian_exp_group({"dataset":["cifar100"], "model":["resnet34_100", "densenet121_100"], "loss_func": ["softmax_loss"], "opt": opt_list, "acc_func":["softmax_accuracy"], "batch_size":[128], "max_epoch":[200], "runs":run_list}) ) EXP_GROUPS['cifar'] = hu.cartesian_exp_group({"dataset":["cifar10"], "model":["resnet34"], "loss_func": ["softmax_loss"], "opt": opt_list + [{'name':"sps", "c":c, 'adapt_flag':'smooth_iter', 'centralize_grad':True}] , "acc_func":["softmax_accuracy"], "batch_size":[128], "max_epoch":[200], "runs":[0]}) # define non-interpolation exp groups eta_max_list = [1, 5, 100] c_list = [0.5] sps_l2_list = [] for c, eta_max in itertools.product(c_list, eta_max_list): sps_l2_list += [{'name':"sps", "c":c, 'fstar_flag':True, 'eps':0, 'adapt_flag':'constant', 'eta_max':eta_max}] sps_list = [] for c, eta_max in itertools.product(c_list, eta_max_list): sps_list += [{'name':"sps", "c":c, 'fstar_flag':False, 'eps':0, 'adapt_flag':'constant', 'eta_max':eta_max}] sgd_list = [{'name':"sgd", "lr":10.0},{'name':"sgd", "lr":1.0}, {'name':"sgd", "lr":1e-3}, {'name':"sgd", "lr":1e-1}, {'name':"sgd", "lr":1e-2}] EXP_GROUPS['syn_l2'] = (hu.cartesian_exp_group({"dataset":['syn'], "model":["logistic"], "loss_func": [ 'logistic_l2_loss', ], "acc_func": ["logistic_accuracy"], "opt": sps_l2_list + sgd_list, "batch_size":[1], "max_epoch":[50], "runs":run_list})) EXP_GROUPS['syn'] = (hu.cartesian_exp_group({"dataset":['syn'], "model":["logistic"], "loss_func": [ 'logistic_loss', ], "acc_func": ["logistic_accuracy"], "opt": sps_list + sgd_list, "batch_size":[1], "max_epoch":[50], "runs":run_list}))

[ "issam.laradji@gmail.com" ]

issam.laradji@gmail.com

5fbdd4faeaa02752c91f94d6860761a2dfb07bac

48e124e97cc776feb0ad6d17b9ef1dfa24e2e474

/sdk/python/pulumi_azure_native/datashare/v20181101preview/get_adls_gen2_file_system_data_set.py

6a6d525b551e637a119b660529a00a01bd625ef0

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

permissive

bpkgoud/pulumi-azure-native

0817502630062efbc35134410c4a784b61a4736d

a3215fe1b87fba69294f248017b1591767c2b96c

refs/heads/master

2023-08-29T22:39:49.984212

2021-11-15T12:43:41

null

0

null

UTF-8

Python

false

7,350

py

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities __all__ = [ 'GetADLSGen2FileSystemDataSetResult', 'AwaitableGetADLSGen2FileSystemDataSetResult', 'get_adls_gen2_file_system_data_set', 'get_adls_gen2_file_system_data_set_output', ] @pulumi.output_type class GetADLSGen2FileSystemDataSetResult: """ An ADLS Gen 2 file system data set. """ def __init__(__self__, data_set_id=None, file_system=None, id=None, kind=None, name=None, resource_group=None, storage_account_name=None, subscription_id=None, type=None): if data_set_id and not isinstance(data_set_id, str): raise TypeError("Expected argument 'data_set_id' to be a str") pulumi.set(__self__, "data_set_id", data_set_id) if file_system and not isinstance(file_system, str): raise TypeError("Expected argument 'file_system' to be a str") pulumi.set(__self__, "file_system", file_system) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if kind and not isinstance(kind, str): raise TypeError("Expected argument 'kind' to be a str") pulumi.set(__self__, "kind", kind) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if resource_group and not isinstance(resource_group, str): raise TypeError("Expected argument 'resource_group' to be a str") pulumi.set(__self__, "resource_group", resource_group) if storage_account_name and not isinstance(storage_account_name, str): raise TypeError("Expected argument 'storage_account_name' to be a str") pulumi.set(__self__, "storage_account_name", storage_account_name) if subscription_id and not isinstance(subscription_id, str): raise TypeError("Expected argument 'subscription_id' to be a str") pulumi.set(__self__, "subscription_id", subscription_id) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter(name="dataSetId") def data_set_id(self) -> str: """ Unique id for identifying a data set resource """ return pulumi.get(self, "data_set_id") @property @pulumi.getter(name="fileSystem") def file_system(self) -> str: """ The file system name. """ return pulumi.get(self, "file_system") @property @pulumi.getter def id(self) -> str: """ The resource id of the azure resource """ return pulumi.get(self, "id") @property @pulumi.getter def kind(self) -> str: """ Kind of data set. Expected value is 'AdlsGen2FileSystem'. """ return pulumi.get(self, "kind") @property @pulumi.getter def name(self) -> str: """ Name of the azure resource """ return pulumi.get(self, "name") @property @pulumi.getter(name="resourceGroup") def resource_group(self) -> str: """ Resource group of storage account """ return pulumi.get(self, "resource_group") @property @pulumi.getter(name="storageAccountName") def storage_account_name(self) -> str: """ Storage account name of the source data set """ return pulumi.get(self, "storage_account_name") @property @pulumi.getter(name="subscriptionId") def subscription_id(self) -> str: """ Subscription id of storage account """ return pulumi.get(self, "subscription_id") @property @pulumi.getter def type(self) -> str: """ Type of the azure resource """ return pulumi.get(self, "type") class AwaitableGetADLSGen2FileSystemDataSetResult(GetADLSGen2FileSystemDataSetResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetADLSGen2FileSystemDataSetResult( data_set_id=self.data_set_id, file_system=self.file_system, id=self.id, kind=self.kind, name=self.name, resource_group=self.resource_group, storage_account_name=self.storage_account_name, subscription_id=self.subscription_id, type=self.type) def get_adls_gen2_file_system_data_set(account_name: Optional[str] = None, data_set_name: Optional[str] = None, resource_group_name: Optional[str] = None, share_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetADLSGen2FileSystemDataSetResult: """ An ADLS Gen 2 file system data set. :param str account_name: The name of the share account. :param str data_set_name: The name of the dataSet. :param str resource_group_name: The resource group name. :param str share_name: The name of the share. """ __args__ = dict() __args__['accountName'] = account_name __args__['dataSetName'] = data_set_name __args__['resourceGroupName'] = resource_group_name __args__['shareName'] = share_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:datashare/v20181101preview:getADLSGen2FileSystemDataSet', __args__, opts=opts, typ=GetADLSGen2FileSystemDataSetResult).value return AwaitableGetADLSGen2FileSystemDataSetResult( data_set_id=__ret__.data_set_id, file_system=__ret__.file_system, id=__ret__.id, kind=__ret__.kind, name=__ret__.name, resource_group=__ret__.resource_group, storage_account_name=__ret__.storage_account_name, subscription_id=__ret__.subscription_id, type=__ret__.type) @_utilities.lift_output_func(get_adls_gen2_file_system_data_set) def get_adls_gen2_file_system_data_set_output(account_name: Optional[pulumi.Input[str]] = None, data_set_name: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, share_name: Optional[pulumi.Input[str]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetADLSGen2FileSystemDataSetResult]: """ An ADLS Gen 2 file system data set. :param str account_name: The name of the share account. :param str data_set_name: The name of the dataSet. :param str resource_group_name: The resource group name. :param str share_name: The name of the share. """ ...

[ "noreply@github.com" ]

bpkgoud.noreply@github.com

1f9ca65ce07629f7f3f5c41490cfa08c638c7723

6ac3e509c9d848497a7cb0f79008ec1f395f3aad

/Phone-Numbers/freecarrierlookup/freecarrierlookup/__main__.py

e28a3cacc22b778073bda4d6b71388e5f2893fbf

[]

no_license

WeilerWebServices/Scrapers

a87ca6c0fd719639be831623b2b55183932d8fba

206ea9adf48e9b882a2d62df691185609483f9d0

refs/heads/master

2022-11-30T10:46:09.731660

2020-08-04T16:07:19

273,375,685

0

null

UTF-8

Python

false

5,091

py

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import argparse import time import csv from sys import stderr, stdout try: import phonenumbers except ImportError: phonenumbers = None from . import FreeCarrierLookup ######################################## # Parse arguments p = argparse.ArgumentParser(description='Lookup carrier information using FreeCarrierLookup.com') if phonenumbers: p.add_argument('phone_number', nargs='+', type=str.strip, help='Phone number to lookup') p.add_argument('--region', default='US', help='libphonenumbers dialing region (default %(default)r)') x = p.add_mutually_exclusive_group() x.add_argument('--cc', type=str.strip, help='Default country code (if none, all numbers must be in E.164 format)') x.add_argument('-E', '--assume-e164', action='store_true', help="Assume E.164 format even if leading '+' not present") else: p.description += '''; phonenumbers module not available (https://github.com/daviddrysdale/python-phonenumbers), so country code must be explicitly specified.''' p.add_argument('phone_number', nargs='+', type=str.strip, help='Phone number to lookup (without country code)') p.add_argument('--cc', type=str.strip, required=True, help='Country code for all numbers') p.add_argument('-o','--output', type=argparse.FileType('w'), default=stdout, help='Output file (default is stdout)') p.add_argument('-c','--csv', action='store_true', help='Output results in CSV format') p.add_argument('-u', '--user-agent', help="User-Agent string (default is none)") p.add_argument('-r', '--rate-limit', type=int, help="Rate limit in seconds per query (default is none)") p.add_argument('--proxy', help='HTTPS proxy (in any format accepted by python-requests, e.g. socks5://localhost:8080)') args = p.parse_args() fcl = FreeCarrierLookup(args.user_agent) csvwr = None if args.proxy: fcl.session.proxies['https'] = args.proxy # Lookup phone numbers' carriers rate_allow = None for pn in args.phone_number: if phonenumbers: # parse into country code and "national number" with phonenumbers if not pn.startswith('+'): if args.cc: pn = '+%s %s' % (args.cc, pn) elif args.assume_e164: pn = '+' + pn try: obj = phonenumbers.parse(pn, region=args.region) cc, phonenum = obj.country_code, ('0'*(obj.number_of_leading_zeros or obj.italian_leading_zero or 0)) + str(obj.national_number) except phonenumbers.NumberParseException as e: print("WARNING: Could not parse %r with phonenumbers: %s" % (pn, ' '.join(e.args)), file=stderr) continue else: # use country code and phone number as-is if pn.startswith('+'): print("WARNING: Skipping %r, which has an E.164 country code prefix (can't parse without phonenumbers module)" % pn, file=stderr) continue cc, phonenum = args.cc, ''.join(filter(str.isdigit, pn)) # Request (web interface includes test=456 and sessionlogin=0, but they don't seem to be required) if args.rate_limit: now = time.time() if rate_allow and now < rate_allow: time.sleep(rate_allow - now) rate_allow = time.time() + args.rate_limit retry = True while retry: retry = False try: im, prompt = fcl.get_captcha() captcha = None if prompt: print("CAPTCHA prompt: %s" % prompt, file=stderr) captcha = input("CAPTCHA response (leave blank to show image)? ") else: print("Couldn't parse CAPTCHA prompt, showing image", file=stderr) if not captcha: im.show() captcha = input("CAPTCHA response? ") results = fcl.lookup(cc, phonenum, captcha) except RuntimeError as e: status, strings = e.args if status == 'error' and 'quota' in strings[0].lower(): p.error('exceeded quota') elif status == 'error' and 'captcha' in strings[0].lower(): print('Incorrect CAPTCHA response. Retry with new CAPTCHA', file=stderr) retry = True else: print('%s received for +%s %s: %s' % (status.title(), cc, phonenum, ' '.join(strings)), file=stderr) except Exception as e: p.error('\n'.join(map(str, e.args))) else: if args.csv: if csvwr is None: csvwr = csv.writer(args.output) csvwr.writerow(('Country Code', 'Phone Number', 'Carrier', 'Is Wireless', 'SMS Gateway Address', 'MMS Gateway Address', 'Note', 'Extra')) csvwr.writerow((cc, phonenum, results.pop('Carrier', None), results.pop('Is Wireless', None), results.pop('SMS Gateway Address',None), results.pop('MMS Gateway Address',None), results.pop('Note',None), results or None)) else: print('+%s %s: %s' % (cc, phonenum, results), file=args.output) p.exit()

[ "nateweiler84@gmail.com" ]

nateweiler84@gmail.com

50ffb4956388901f75c430e335b4c03a8493463b

d748710c6c5fa0f61b5bd6c2ec849d9250428811

/demo1/client_python/test/test_format.py

a03e8a252d7c7c1a5ae10dea8b78b8c22f086cd7

[]

no_license

stefan2904/aries-experiments

9f4dab2d0711b76557e3d6ae8e5a27e532102685

46f31ee62cf951da2696e5ca4e6dc1d3d753743d

refs/heads/main

2023-03-23T00:06:06.362992

2021-03-18T12:56:58

329,986,417

1

0

null

UTF-8

Python

false

902

py

# coding: utf-8 """ (Aries Agent REST Server) of VC4SM University. No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501 OpenAPI spec version: 0.1.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import swagger_client from swagger_client.models.format import Format # noqa: E501 from swagger_client.rest import ApiException class TestFormat(unittest.TestCase): """Format unit test stubs""" def setUp(self): pass def tearDown(self): pass def testFormat(self): """Test Format""" # FIXME: construct object with mandatory attributes with example values # model = swagger_client.models.format.Format() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "dev@2904.cc" ]

dev@2904.cc

4befa60f75f65fc7d117fd7196c46db4398c2c4c

f99cca94f74c69bc518e298c14140534e18eabd3

/OrcApi/start_report.py

efcbc2ca473ffe5c686fdeb3c906e7f559f6ecab

[]

no_license

pubselenium/OrcTestToolsKit

d6d838d9937d2c4d86941e317cb3ff096b58e52d

f3ccbbceaed4f4996f6907a2f4880c2fd3f82bbb

refs/heads/master

2021-04-29T05:15:53.240714

2016-12-30T09:42:53

null

0

null

UTF-8

Python

false

832

py

# coding=utf-8 import sys from flask import make_response from OrcLib import init_log from OrcLib import get_config from OrcApi import app from OrcApi import orc_api from OrcApi.Run.ReportApi import ReportDetAPI configer = get_config("server") @app.after_request def after_request(response): response.headers['Access-Control-Allow-Origin'] = '*' return response @orc_api.representation("text/html") def out_html(data, code, headers=None): resp = make_response(data, code) resp.headers.extend(headers or {}) return resp # Widget orc_api.add_resource(ReportDetAPI, '/api/1.0/Report/<string:p_id>/<string:p_time>', endpoint='Report') driver_host = configer.get_option("REPORT", "ip") driver_port = configer.get_option("REPORT", "port") reload(sys) init_log() app.run(host=driver_host, port=driver_port)

[ "orange21cn@126.com" ]

orange21cn@126.com

53cde0b836010d45228fa1c3b0df4ed331fc4563

0bde5f7f09aa537ed1f4828d4e5ebee66475918f

/h2o-py/tests/testdir_apis/Data_Manipulation/pyunit_h2oH2OFrame_split_frame.py

7b6184fc5c776b24ad32cc3e4da703f2af126c3c

[ "Apache-2.0" ]

permissive

Winfredemalx54/h2o-3

d69f1c07e1f5d2540cb0ce5e6073415fa0780d32

dfb163c82ff3bfa6f88cdf02465a9bb4c8189cb7

refs/heads/master

2022-12-14T08:59:04.109986

2020-09-23T08:36:59

297,947,978

2

0

Apache-2.0

2020-09-23T11:28:54

null

UTF-8

Python

false

1,086

py

from __future__ import print_function import sys sys.path.insert(1,"../../../") from tests import pyunit_utils import h2o import numpy as np from h2o.utils.typechecks import assert_is_type from h2o.frame import H2OFrame def h2o_H2OFrame_split_frame(): """ Python API test: h2o.frame.H2OFrame.split_frame(ratios=None, destination_frames=None, seed=None) """ python_lists = np.random.uniform(-1,1, (10000,2)) h2oframe = h2o.H2OFrame(python_obj=python_lists) newframe = h2oframe.split_frame(ratios=[0.5, 0.25], destination_frames=["f1", "f2", "f3"], seed=None) assert_is_type(newframe, list) assert_is_type(newframe[0], H2OFrame) assert len(newframe)==3, "h2o.H2OFrame.split_frame() command is not working." assert h2oframe.nrow==(newframe[0].nrow+newframe[1].nrow+newframe[2].nrow), "h2o.H2OFrame.split_frame() command " \ "is not working." if __name__ == "__main__": pyunit_utils.standalone_test(h2o_H2OFrame_split_frame()) else: h2o_H2OFrame_split_frame()

[ "noreply@github.com" ]

Winfredemalx54.noreply@github.com

5953b3b9c01500579a6f297e7f5b22fd87d779c5

2bb90b620f86d0d49f19f01593e1a4cc3c2e7ba8

/pardus/playground/ebayer/c2/kernel/pae/drivers/module-pae-openafs/actions.py

5dcbf53a4428541a79d686435aaf1aa6a77d6da8

[]

no_license

aligulle1/kuller

bda0d59ce8400aa3c7ba9c7e19589f27313492f7

7f98de19be27d7a517fe19a37c814748f7e18ba6

refs/heads/master

2021-01-20T02:22:09.451356

2013-07-23T17:57:58

null

0

null

UTF-8

Python

false

796

py

#!/usr/bin/python # -*- coding: utf-8 -*- # # Copyright 2010 TUBITAK/UEKAE # Licensed under the GNU General Public License, version 2. # See the file http://www.gnu.org/licenses/old-licenses/gpl-2.0.txt from pisi.actionsapi import shelltools from pisi.actionsapi import autotools from pisi.actionsapi import pisitools from pisi.actionsapi import get from pisi.actionsapi import kerneltools KDIR = kerneltools.getKernelVersion() WorkDir = "openafs-%s" % get.srcVERSION() def setup(): autotools.configure("--with-linux-kernel-headers=/lib/modules/%s/build" % KDIR) def build(): autotools.make("-j1 only_libafs") def install(): for m in ("libafs.ko", "afspag.ko"): pisitools.insinto("/lib/modules/%s/kernel/extra/openafs" % KDIR, "src/libafs/MODLOAD-%s-SP/%s" % (KDIR, m))

[ "yusuf.aydemir@istanbul.com" ]

yusuf.aydemir@istanbul.com

6e00615762e8df542d13ee65b1357bdf9cf232dc

a11984110d22e8231896c7e8bf2c6c2a96e46502

/Daily Challenges/2020/June/Coin Change 2.py

11def6bdf3936bba8f8e65cab5a71696240db825

[]

no_license

Waqar-107/LeetCode

fbd323c89a5ea010b3322b0b35dd087a7744abc4

5f7dc48918c0367b20e733830e9807eb40840f77

refs/heads/master

2023-08-03T12:27:58.593051

2023-07-24T01:33:24

220,239,559

8

7

null

2022-05-01T18:50:03

2019-11-07T13:08:48

Python

UTF-8

Python

false

837

py

class Solution: def change(self, amount: int, coins: List[int]) -> int: n = len(coins) dp = [[0 for _ in range(n)] for _ in range(amount + 1)] if amount == 0: return 1 if n == 0: return 0 for j in range(n): dp[0][j] = 1 for i in range(1, amount + 1): for j in range(n): # include coin j if i - coins[j] >= 0: x = dp[i - coins[j]][j] else: x = 0 # do not include j if j >= 1: y = dp[i][j - 1] else: y = 0 dp[i][j] = x + y return dp[amount][n - 1]

[ "noreply@github.com" ]

Waqar-107.noreply@github.com

0a6b8b51c8c6d0be55dbbec18662c723561424b8

44064ed79f173ddca96174913910c1610992b7cb

/Second_Processing_app/temboo/Library/SendGrid/WebAPI/Profile/__init__.py

6d92d7a013674c733657f66763ff162be16e38d5

[]

no_license

dattasaurabh82/Final_thesis

440fb5e29ebc28dd64fe59ecd87f01494ed6d4e5

8edaea62f5987db026adfffb6b52b59b119f6375

refs/heads/master

2021-01-20T22:25:48.999100

2014-10-14T18:58:00

null

0

null

UTF-8

Python

false

172

py

from UpdateContactProfileEmailAddress import * from UpdateUsername import * from ViewAccountProfile import * from ResetPassword import * from UpdateAccountProfile import *

[ "dattasaurabh82@gmail.com" ]

dattasaurabh82@gmail.com

4ddb79704d7f95d929525eb9514d2329a0e2ae5f

9ce4292954000fd66bcdbd0797a280c306308d08

/quizzes/00.organize.me/Cracking the Coding Interview/10-5.py

b766c70b7b543f695e10a7a7269d68734ca8f968

[ "MIT" ]

permissive

JiniousChoi/encyclopedia-in-code

0c786f2405bfc1d33291715d9574cae625ae45be

77bc551a03a2a3e3808e50016ece14adb5cfbd96

refs/heads/master

2021-06-27T07:50:10.789732

2020-05-29T12:50:46

137,426,553

2

0

MIT

2020-10-13T08:56:12

2018-06-15T01:29:31

Python

UTF-8

Python

false

1,342

py

''' 10.5 - 빈 문자열이 섞여 있는 정렬 상태의 배열이 주어졌을 때, 특정한 문자열 의 위치를 찾는 메서드를 작성하라. ''' def search_arr_with_empty_string(arr, target): assert arr left = init_left(arr) right = init_right(arr) mid = get_mid(arr, left, right) while mid>=0: if arr[mid]==target: return mid if arr[mid]>target: right=mid elif arr[mid]<target: left=mid else: assert False mid = get_mid(arr, left, right) return -1 def init_left(arr): for i,e in enumerate(arr): if e: return i raise Exception("주어진 배열이 빈문자열로만 차있습니다") def init_right(arr): for i in range(len(arr)-1, -1, -1): if arr[i]: return i raise Exception("주어진 배열이 빈문자열로만 차있습니다") def get_mid(arr, left, right): assert left < right mid = (left+right)//2 if arr[mid]: return mid for t in range(mid-1, left, -1): if arr[t]: return t for t in range(mid+1, right): if arr[t]: return t return -1 sample_arr = ["at","","","","ball","","","car","","","dad","",""] idx = search_arr_with_empty_string(sample_arr, "ball") print(idx)

[ "jinchoiseoul@gmail.com" ]

jinchoiseoul@gmail.com

dcbab961672293df7685c2b68b386d61314c7e39

53fab060fa262e5d5026e0807d93c75fb81e67b9

/backup/user_144/ch149_2020_04_13_20_40_50_766295.py

878ea953ff527f041b48cc86231d9d5b082aeda2

[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

01940ab0897aa6005764fc220b900e4d6161d36b

refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

306,735,108

0

null

UTF-8

Python

false

1,029

py

salario_bruto = int(input(("Salario: ")) numero_dependentes = int(input("Dependentes: ")) contri_INSS = 0 if salario_bruto <= 1045: contri_INSS = salario_bruto * 0.075 elif salario_bruto >= 1045.01 and salario_bruto <=2089.60: contri_INSS = salario_bruto * 0.09 elif salario_bruto >= 2089.01 and salario_bruto <= 3134.40: contri_INSS = salario_bruto * 0.12 elif salario_bruto >= 3134.41 and salario_bruto <=6101.06: contri_INSS = salario_bruto * 0.14 else: contri_INSS = 671.12 base = salario_bruto - contri_INSS - (numero_dependentes* 189.59) aliquota = 0 deducao = 0 if base <= 1903.98: aliquota = 0 deducao = 0 elif base >= 1903.99 and base <= 2826.65: aliquota = 0.75 deducao = 142.80 elif base >= 2826.66 and base <= 3751.05: aliquota = 0.15 deducao = 354.80 elif base >= 3751.06 and base <= 4664.68: aliquota = 0.225 deducao = 636.13 else: aliquota = 0.275 deducao = 869.36 IRRF = base * aliquota - deducao print(IRRF)

[ "you@example.com" ]

you@example.com

c1825c451ebce3e5a90f216fa0ea0683c035ad0d

34f6d9a4c4becc057d1b01a0ed3e50f20a071b03

/main/migrations/0001_initial.py

55e4c7b7da9e0f6d8dea069a8d80d7bc81e61042

[]

no_license

hitscanner/WUW

e6d59bb8eae3834cf115e50834a2a4af51c29b29

31a482afe3e4789c979696a70f5ded17488b7810

refs/heads/master

2022-12-10T06:01:01.862354

2019-08-11T11:31:01

196,556,732

0

null

2022-07-06T20:13:05

2019-07-12T10:06:49

JavaScript

UTF-8

Python

false

771

py

# Generated by Django 2.2 on 2019-07-16 08:45 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Search_result', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=100)), ('poster', models.ImageField(blank=True, upload_to='')), ('heart', models.ImageField(blank=True, upload_to='')), ('created_at', models.DateField(auto_now_add=True)), ('updated_at', models.DateField(auto_now=True)), ], ), ]

[ "dmswl_0311@naver.com" ]

dmswl_0311@naver.com

cab7d49da20714d35bcfe777d586c4c4b8e8bcb1

3c000380cbb7e8deb6abf9c6f3e29e8e89784830

/venv/Lib/site-packages/cobra/modelimpl/eqpt/spcmnblk.py

4a85bd179a0f4e21e2c358232362a472c0383c4d

[]

no_license

bkhoward/aciDOM

91b0406f00da7aac413a81c8db2129b4bfc5497b

f2674456ecb19cf7299ef0c5a0887560b8b315d0

refs/heads/master

2023-03-27T23:37:02.836904

2021-03-26T22:07:54

351,855,399

0

null

UTF-8

Python

false

8,084

py

# coding=UTF-8 # ********************************************************************** # Copyright (c) 2013-2020 Cisco Systems, Inc. All rights reserved # written by zen warriors, do not modify! # ********************************************************************** from cobra.mit.meta import ClassMeta from cobra.mit.meta import StatsClassMeta from cobra.mit.meta import CounterMeta from cobra.mit.meta import PropMeta from cobra.mit.meta import Category from cobra.mit.meta import SourceRelationMeta from cobra.mit.meta import NamedSourceRelationMeta from cobra.mit.meta import TargetRelationMeta from cobra.mit.meta import DeploymentPathMeta, DeploymentCategory from cobra.model.category import MoCategory, PropCategory, CounterCategory from cobra.mit.mo import Mo # ################################################## class SpCmnBlk(Mo): """ A SPROM common block. """ meta = ClassMeta("cobra.model.eqpt.SpCmnBlk") meta.moClassName = "eqptSpCmnBlk" meta.rnFormat = "spcmn" meta.category = MoCategory.REGULAR meta.label = "Sprom Common Block" meta.writeAccessMask = 0x80080000000001 meta.readAccessMask = 0x80080000000001 meta.isDomainable = False meta.isReadOnly = True meta.isConfigurable = False meta.isDeletable = False meta.isContextRoot = False meta.parentClasses.add("cobra.model.eqpt.SpromFan") meta.parentClasses.add("cobra.model.eqpt.SpromLc") meta.parentClasses.add("cobra.model.eqpt.SpromSup") meta.parentClasses.add("cobra.model.eqpt.SpromPsu") meta.parentClasses.add("cobra.model.eqpt.SpromBP") meta.superClasses.add("cobra.model.eqpt.SpBlkHdr") meta.rnPrefixes = [ ('spcmn', False), ] prop = PropMeta("str", "childAction", "childAction", 4, PropCategory.CHILD_ACTION) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop._addConstant("deleteAll", "deleteall", 16384) prop._addConstant("deleteNonPresent", "deletenonpresent", 8192) prop._addConstant("ignore", "ignore", 4096) meta.props.add("childAction", prop) prop = PropMeta("str", "cksum", "cksum", 3358, PropCategory.REGULAR) prop.label = "Checksum" prop.isImplicit = True prop.isAdmin = True meta.props.add("cksum", prop) prop = PropMeta("str", "clei", "clei", 3375, PropCategory.REGULAR) prop.label = "CLEI Code" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("clei", prop) prop = PropMeta("str", "count", "count", 3360, PropCategory.REGULAR) prop.label = "Block Count" prop.isImplicit = True prop.isAdmin = True meta.props.add("count", prop) prop = PropMeta("str", "dn", "dn", 1, PropCategory.DN) prop.label = "None" prop.isDn = True prop.isImplicit = True prop.isAdmin = True prop.isCreateOnly = True meta.props.add("dn", prop) prop = PropMeta("str", "engBits", "engBits", 3372, PropCategory.REGULAR) prop.label = "Engineering Bits" prop.isImplicit = True prop.isAdmin = True meta.props.add("engBits", prop) prop = PropMeta("str", "hwRevMaj", "hwRevMaj", 3369, PropCategory.REGULAR) prop.label = "Hardware Revision Major Number" prop.isImplicit = True prop.isAdmin = True meta.props.add("hwRevMaj", prop) prop = PropMeta("str", "hwRevMin", "hwRevMin", 3370, PropCategory.REGULAR) prop.label = "Hardware Revision Minor Number" prop.isImplicit = True prop.isAdmin = True meta.props.add("hwRevMin", prop) prop = PropMeta("str", "len", "len", 3357, PropCategory.REGULAR) prop.label = "Length" prop.isImplicit = True prop.isAdmin = True meta.props.add("len", prop) prop = PropMeta("str", "major", "major", 3361, PropCategory.REGULAR) prop.label = "FRU Major Number" prop.isImplicit = True prop.isAdmin = True meta.props.add("major", prop) prop = PropMeta("str", "mfgBits", "mfgBits", 3371, PropCategory.REGULAR) prop.label = "Manufacturing Bits" prop.isImplicit = True prop.isAdmin = True meta.props.add("mfgBits", prop) prop = PropMeta("str", "mfgDev", "mfgDev", 3368, PropCategory.REGULAR) prop.label = "Manufacturing Deviation" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("mfgDev", prop) prop = PropMeta("str", "minor", "minor", 3362, PropCategory.REGULAR) prop.label = "FRU Minor Number" prop.isImplicit = True prop.isAdmin = True meta.props.add("minor", prop) prop = PropMeta("str", "modTs", "modTs", 7, PropCategory.REGULAR) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop.defaultValue = 0 prop.defaultValueStr = "never" prop._addConstant("never", "never", 0) meta.props.add("modTs", prop) prop = PropMeta("str", "oem", "oem", 3363, PropCategory.REGULAR) prop.label = "OEM" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("oem", prop) prop = PropMeta("str", "pRev", "pRev", 3367, PropCategory.REGULAR) prop.label = "Part Revision" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("pRev", prop) prop = PropMeta("str", "pdNum", "pdNum", 3364, PropCategory.REGULAR) prop.label = "Product Number" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("pdNum", prop) prop = PropMeta("str", "prtNum", "prtNum", 3366, PropCategory.REGULAR) prop.label = "Part Number" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("prtNum", prop) prop = PropMeta("str", "pwrCon", "pwrCon", 3373, PropCategory.REGULAR) prop.label = "Power Consumption" prop.isImplicit = True prop.isAdmin = True meta.props.add("pwrCon", prop) prop = PropMeta("str", "ramFl", "ramFl", 3374, PropCategory.REGULAR) prop.label = "RMA Failure Code" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("ramFl", prop) prop = PropMeta("str", "rn", "rn", 2, PropCategory.RN) prop.label = "None" prop.isRn = True prop.isImplicit = True prop.isAdmin = True prop.isCreateOnly = True meta.props.add("rn", prop) prop = PropMeta("str", "serNum", "serNum", 3365, PropCategory.REGULAR) prop.label = "Serial Number" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("serNum", prop) prop = PropMeta("str", "sig", "sig", 3355, PropCategory.REGULAR) prop.label = "Signature" prop.isImplicit = True prop.isAdmin = True meta.props.add("sig", prop) prop = PropMeta("str", "size", "size", 3359, PropCategory.REGULAR) prop.label = "Block Size" prop.isImplicit = True prop.isAdmin = True meta.props.add("size", prop) prop = PropMeta("str", "status", "status", 3, PropCategory.STATUS) prop.label = "None" prop.isImplicit = True prop.isAdmin = True prop._addConstant("created", "created", 2) prop._addConstant("deleted", "deleted", 8) prop._addConstant("modified", "modified", 4) meta.props.add("status", prop) prop = PropMeta("str", "vdrId", "vdrId", 3376, PropCategory.REGULAR) prop.label = "Vendor ID" prop.isImplicit = True prop.isAdmin = True prop.range = [(0, 512)] meta.props.add("vdrId", prop) prop = PropMeta("str", "ver", "ver", 3356, PropCategory.REGULAR) prop.label = "Version" prop.isImplicit = True prop.isAdmin = True meta.props.add("ver", prop) # Deployment Meta meta.deploymentQuery = True meta.deploymentType = "Ancestor" meta.deploymentQueryPaths.append(DeploymentPathMeta("EqptSlotToEPg", "EPG", "cobra.model.fv.EPg")) def __init__(self, parentMoOrDn, markDirty=True, **creationProps): namingVals = [] Mo.__init__(self, parentMoOrDn, markDirty, *namingVals, **creationProps) # End of package file # ##################################################

[ "bkhoward@live.com" ]

bkhoward@live.com

877d1c526b3f20bd3188f83451ed138f7a56e486

9743d5fd24822f79c156ad112229e25adb9ed6f6

/xai/brain/wordbase/otherforms/_sniggering.py

17cd2b9a2bb4518486b4ed491fb93307ec1d284d

[ "MIT" ]

permissive

cash2one/xai

de7adad1758f50dd6786bf0111e71a903f039b64

e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6

refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

null

0

null

UTF-8

Python

false

230

py

#calss header class _SNIGGERING(): def __init__(self,): self.name = "SNIGGERING" self.definitions = snigger self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['snigger']

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

ac7098eb210e84d502ecbef2178e0288d257fa61

010215c1421f5275a846e7154189b22cdd3c89bc

/MS/Two Pointer/backspace_compare.py

b930b074d11fe2ed02fd6c809b5f4f8223bf58ac

[]

no_license

bsextion/CodingPractice_Py

ab54d5715298645a8fd7ab6945bf3b22d4e6a874

da2847a04705394c32a6fe1b5f6c6b64c24647a3

refs/heads/master

2023-08-16T17:14:47.643989

2021-09-28T19:23:40

383,658,966

0

null

UTF-8

Python

false

644

py

def backspace_compare(str1:str, str2): #two pointers, ptr_one = 0 ptr_two = 0 while ptr_one < len(str1): if str1[ptr_one] is '#' and ptr_one > 0: temp = list(str1) temp[ptr_one-1] = '' temp[ptr_one] = '' str1 = ''.join(temp) ptr_one += 1 while ptr_two < len(str2): if str2[ptr_two] is '#' and ptr_two > 0: temp = list(str2) temp[ptr_two - 1] = '' temp[ptr_two] = '' str2 = ''.join(temp) ptr_two += 1 if str1 == str2: return True return False backspace_compare("xp#", "xyz##")

[ "bsextion@gmail.com" ]

bsextion@gmail.com

b6677daaa5433a1a5bff104dbd781005f9caa6ad

bdba52c756cc09f192b720ea318510c265665dcd

/swagger_client/models/get_characters_character_id_planets_planet_id_head.py

d6daf4f3b6cdc6f78e96cc5957b82e43bb1a5d74

[ "MIT" ]

permissive

rseichter/bootini-star

6b38195890f383615cc2b422c365ac28c5b87292

a80258f01a05e4df38748b8cb47dfadabd42c20d

refs/heads/master

2020-03-14T03:17:11.385048

2018-06-28T17:23:23

131,416,504

0

MIT

2018-05-01T14:26:04

2018-04-28T14:28:46

Python

UTF-8

Python

false

5,555

py

# coding: utf-8 """ EVE Swagger Interface An OpenAPI for EVE Online # noqa: E501 OpenAPI spec version: 0.8.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six class GetCharactersCharacterIdPlanetsPlanetIdHead(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'head_id': 'int', 'latitude': 'float', 'longitude': 'float' } attribute_map = { 'head_id': 'head_id', 'latitude': 'latitude', 'longitude': 'longitude' } def __init__(self, head_id=None, latitude=None, longitude=None): # noqa: E501 """GetCharactersCharacterIdPlanetsPlanetIdHead - a model defined in Swagger""" # noqa: E501 self._head_id = None self._latitude = None self._longitude = None self.discriminator = None self.head_id = head_id self.latitude = latitude self.longitude = longitude @property def head_id(self): """Gets the head_id of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 head_id integer # noqa: E501 :return: The head_id of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 :rtype: int """ return self._head_id @head_id.setter def head_id(self, head_id): """Sets the head_id of this GetCharactersCharacterIdPlanetsPlanetIdHead. head_id integer # noqa: E501 :param head_id: The head_id of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 :type: int """ if head_id is None: raise ValueError("Invalid value for `head_id`, must not be `None`") # noqa: E501 if head_id is not None and head_id > 9: # noqa: E501 raise ValueError("Invalid value for `head_id`, must be a value less than or equal to `9`") # noqa: E501 if head_id is not None and head_id < 0: # noqa: E501 raise ValueError("Invalid value for `head_id`, must be a value greater than or equal to `0`") # noqa: E501 self._head_id = head_id @property def latitude(self): """Gets the latitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 latitude number # noqa: E501 :return: The latitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 :rtype: float """ return self._latitude @latitude.setter def latitude(self, latitude): """Sets the latitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. latitude number # noqa: E501 :param latitude: The latitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 :type: float """ if latitude is None: raise ValueError("Invalid value for `latitude`, must not be `None`") # noqa: E501 self._latitude = latitude @property def longitude(self): """Gets the longitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 longitude number # noqa: E501 :return: The longitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 :rtype: float """ return self._longitude @longitude.setter def longitude(self, longitude): """Sets the longitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. longitude number # noqa: E501 :param longitude: The longitude of this GetCharactersCharacterIdPlanetsPlanetIdHead. # noqa: E501 :type: float """ if longitude is None: raise ValueError("Invalid value for `longitude`, must not be `None`") # noqa: E501 self._longitude = longitude def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, GetCharactersCharacterIdPlanetsPlanetIdHead): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "github@seichter.de" ]

github@seichter.de

c4f36d4b7fa6d6a4966f1a22288517df1842a6e4

480e33f95eec2e471c563d4c0661784c92396368

/Configuration/Generator/python/QCD_Pt-20toInf_MuEnrichedPt15_TuneCUETP8M1_13TeV_pythia8_cff.py

7ca22905e2e7cd1528d55e528353b0c20e2ccb2d

[ "Apache-2.0" ]

permissive

cms-nanoAOD/cmssw

4d836e5b76ae5075c232de5e062d286e2026e8bd

4eccb8a758b605875003124dd55ea58552b86af1

refs/heads/master-cmsswmaster

2021-01-23T21:19:52.295420

2020-08-27T08:01:20

102,867,729

7

14

Apache-2.0

2022-05-23T07:58:09

2017-09-08T14:03:57

C++

UTF-8

Python

false

2,277

py

import FWCore.ParameterSet.Config as cms from Configuration.Generator.Pythia8CommonSettings_cfi import * from Configuration.Generator.Pythia8CUEP8M1Settings_cfi import * generator = cms.EDFilter("Pythia8GeneratorFilter", maxEventsToPrint = cms.untracked.int32(1), pythiaPylistVerbosity = cms.untracked.int32(1), filterEfficiency = cms.untracked.double(0.00042), pythiaHepMCVerbosity = cms.untracked.bool(False), comEnergy = cms.double(13000.0), crossSection = cms.untracked.double(7.20648e+08), PythiaParameters = cms.PSet( pythia8CommonSettingsBlock, pythia8CUEP8M1SettingsBlock, processParameters = cms.vstring( 'ParticleDecays:limitTau0 = off', 'ParticleDecays:limitCylinder = on', 'ParticleDecays:xyMax = 2000', 'ParticleDecays:zMax = 4000', 'HardQCD:all = on', 'PhaseSpace:pTHatMin = 20', '130:mayDecay = on', '211:mayDecay = on', '321:mayDecay = on' ), parameterSets = cms.vstring('pythia8CommonSettings', 'pythia8CUEP8M1Settings', 'processParameters', ) ) ) mugenfilter = cms.EDFilter("MCSmartSingleParticleFilter", MinPt = cms.untracked.vdouble(15.,15.), MinEta = cms.untracked.vdouble(-2.5,-2.5), MaxEta = cms.untracked.vdouble(2.5,2.5), ParticleID = cms.untracked.vint32(13,-13), Status = cms.untracked.vint32(1,1), # Decay cuts are in mm MaxDecayRadius = cms.untracked.vdouble(2000.,2000.), MinDecayZ = cms.untracked.vdouble(-4000.,-4000.), MaxDecayZ = cms.untracked.vdouble(4000.,4000.) ) configurationMetadata = cms.untracked.PSet( version = cms.untracked.string('\$Revision$'), name = cms.untracked.string('\$Source$'), annotation = cms.untracked.string('QCD dijet production, pThat > 20 GeV, with INCLUSIVE muon preselection (pt(mu) > 15 GeV), 13 TeV, TuneCUETP8M1') ) ProductionFilterSequence = cms.Sequence(generator*mugenfilter)

[ "kpedro88@gmail.com" ]

kpedro88@gmail.com

ba2213f9f76fd58af80066c34ca0933cca61dfbe

8b2b497069ed3db150e15863559dc0e9a44dc8c1

/pure_protobuf/io/url.py

3e2004fb24b0f96f02a7ce5efe77d39b2a72b5a2

[ "MIT" ]

permissive

eigenein/protobuf

2aec2c544cf9f6571b161b1e62ec3675a5b141eb

cf14bc702302c9334c7c9cc839b0b24334a725ef

refs/heads/master

2023-08-31T21:23:29.258800

2023-08-27T12:00:26

2023-08-28T12:36:25

1,890,285

216

20

MIT

2023-09-13T12:58:54

2011-06-13T18:26:55

Python

UTF-8

Python

false

619

py

"""Reading and writing parsed URLs.""" from typing import IO, Iterator from urllib.parse import ParseResult, urlparse, urlunparse from pure_protobuf.interfaces.read import Read from pure_protobuf.interfaces.write import Write from pure_protobuf.io.bytes_ import read_string, write_string class ReadUrl(Read[ParseResult]): __slots__ = () def __call__(self, io: IO[bytes]) -> Iterator[ParseResult]: yield urlparse(read_string(io)) class WriteUrl(Write[ParseResult]): __slots__ = () def __call__(self, value: ParseResult, io: IO[bytes]) -> None: write_string(urlunparse(value), io)

[ "eigenein@gmail.com" ]

eigenein@gmail.com

aee56c11569ff5461d903c1776810a2242a2f6ce

12c15c7ae150acaf8032f444db24440da2234b1a

/ComputerVision/Projects/cv20_proj1/lap.py

f91c55cde634d08ca8ca04d68cc2380417508879

[]

no_license

Jimut123/rkmveri-labs

315ecd4607af72dd0851489e427a3ab09a8009ff

be19a453ea32460c454e3443798e3d8954fb084b

refs/heads/master

2023-02-02T17:11:23.641187

2020-12-13T18:35:20

201,784,550

2

0

null

UTF-8

Python

false

1,476

py

import numpy as np import cv2 cutoff_frequency = 4 filter = cv2.getGaussianKernel(ksize=cutoff_frequency*4+1, sigma=cutoff_frequency) filter = np.dot(filter, filter.T) def del2(M): dx = 1 dy = 1 rows, cols = M.shape dx = dx * np.ones ((1, cols - 1)) dy = dy * np.ones ((rows-1, 1)) mr, mc = M.shape D = np.zeros ((mr, mc)) if (mr >= 3): ## x direction ## left and right boundary D[:, 0] = (M[:, 0] - 2 * M[:, 1] + M[:, 2]) / (dx[:,0] * dx[:,1]) D[:, mc-1] = (M[:, mc - 3] - 2 * M[:, mc - 2] + M[:, mc-1]) \ / (dx[:,mc - 3] * dx[:,mc - 2]) ## interior points tmp1 = D[:, 1:mc - 1] tmp2 = (M[:, 2:mc] - 2 * M[:, 1:mc - 1] + M[:, 0:mc - 2]) tmp3 = np.kron (dx[:,0:mc -2] * dx[:,1:mc - 1], np.ones ((mr, 1))) D[:, 1:mc - 1] = tmp1 + tmp2 / tmp3 if (mr >= 3): ## y direction ## top and bottom boundary D[0, :] = D[0,:] + \ (M[0, :] - 2 * M[1, :] + M[2, :] ) / (dy[0,:] * dy[1,:]) D[mr-1, :] = D[mr-1, :] \ + (M[mr-3,:] - 2 * M[mr-2, :] + M[mr-1, :]) \ / (dy[mr-3,:] * dx[:,mr-2]) ## interior points tmp1 = D[1:mr-1, :] tmp2 = (M[2:mr, :] - 2 * M[1:mr - 1, :] + M[0:mr-2, :]) tmp3 = np.kron (dy[0:mr-2,:] * dy[1:mr-1,:], np.ones ((1, mc))) D[1:mr-1, :] = tmp1 + tmp2 / tmp3 return D / 4 print(del2(filter))

[ "jimutbahanpal@yahoo.com" ]

jimutbahanpal@yahoo.com

c89b9794cbf2b7f1b847fd4e611f0c42b5aa35fa

4771ca5cd2c7be8e6d0a50f1e0b1f85a17ec5efd

/todos/forms.py

51e119676bbd8af1823a81a48e4933eac9090377

[]

no_license

luanfonceca/todomvc-django-over-the-wire

03aa2e57c04d465c56cf06e1c95b417c502bcbad

ae1b6e989c0c9edd7d4f8de2d9553bf57e4e1e38

refs/heads/main

2023-03-03T19:23:35.849691

2021-02-07T13:23:17

334,795,276

2

0

null

UTF-8

Python

false

272

py

from django import forms from todos.models import ToDo class ToDoForm(forms.ModelForm): class Meta: model = ToDo fields = ('title',) class CompleteToDoForm(forms.ModelForm): class Meta: model = ToDo fields = ('is_completed',)

[ "luanfonceca@gmail.com" ]

luanfonceca@gmail.com

2212a2b636017e168a6d9d41201b0c3c70163ac9

057d662a83ed85897e9906d72ea90fe5903dccc5

/Comprehension.py

68427686ee2e27abe1a3290558f7865fd4fd49bb

[]

no_license

Karishma00/AnsiblePractice

19a4980b1f6cca7b251f2cbea3acf9803db6e016

932558d48869560a42ba5ba3fb72688696e1868a

refs/heads/master

2020-08-05T00:05:31.679220

2019-10-04T13:07:29

212,324,468

0

null

UTF-8

Python

false

150

py

# list=[x**2 for x in range(0,10)] print(list) #another ex celcius=[0,10,30,90] fahrenheiet=[((0/5)*temp +32) for temp in celcius] print(fahrenheiet)

[ "karishma11198@gmail.com" ]

karishma11198@gmail.com

1d806f235836b0b15c4c2615bbf176dff8458479

82be2ebd50fef5b359cfbcacd21f38da4c383ffc

/tests/test_writer.py

a340f79117bfab8297d6e6b0fb63a8be472e2988

[ "BSD-3-Clause" ]

permissive

isabella232/helium-commander

5eae81b89cccf2dae56a4163815d867777387288

58d1fe4064c51beccbff7a0d93bf037fffdac370

refs/heads/master

2021-06-15T15:16:00.139651

2017-02-28T23:22:36

null

0

null

UTF-8

Python

false

1,170

py

from helium_commander import Sensor, DataPoint from itertools import islice import pytest def validate_format(output, client, sensors, capsys): first_sensor = sensors[0] # With sort Sensor.display(client, sensors, format=output, sort='name') out, err = capsys.readouterr() assert first_sensor.short_id in out Sensor.display(client, sensors, format=output, sort='name', reverse=True) reversed, err = capsys.readouterr() assert reversed != out # Without sort Sensor.display(client, sensors, format=output) out, err = capsys.readouterr() assert first_sensor.short_id in out Sensor.display(client, sensors, format=output, reverse=True) reversed, err = capsys.readouterr() assert reversed != out def test_formats(client, sensors, capsys): for output in ['csv', 'tabular', 'json']: validate_format(output, client, sensors, capsys) with pytest.raises(AttributeError): Sensor.display(client, sensors, format='xxx') def test_timeseries(client, authorized_organization): points = islice(authorized_organization.timeseries(), 10) DataPoint.display(client, points, max_width=20)

[ "noreply@github.com" ]

isabella232.noreply@github.com

102a94ec2318f2e1673fd0e494380451db909578

0e7aed5eef2e1d132a7e75dd8f439ae76c87639c

/python/652_find_duplicated_subtrees.py

ee4a673bdc3ecbf54bdd00a403e289703d72c886

[ "MIT" ]

permissive

liaison/LeetCode

2a93df3b3ca46b34f922acdbc612a3bba2d34307

bf03743a3676ca9a8c107f92cf3858b6887d0308

refs/heads/master

2022-09-05T15:04:19.661298

2022-08-19T19:29:19

52,914,957

17

4

null

UTF-8

Python

false

2,429

py

# Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class Solution: def findDuplicateSubtrees(self, root: TreeNode) -> List[TreeNode]: # set of all node strings node_str_set = set() duplicated_strs = set() duplicated_nodes = list() def node2str(node): """ this function accomplishes two tasks: - index each node into a string - search the duplicated nodes during the traversal """ nonlocal node_str_set nonlocal duplicated_strs nonlocal duplicated_nodes if node is None: return "" left_str = node2str(node.left) right_str = node2str(node.right) node_str = str(node.val) + "(" + left_str + ")" + "(" + right_str + ")" if node_str in node_str_set: if node_str not in duplicated_strs: duplicated_strs.add(node_str) duplicated_nodes.append(node) else: node_str_set.add(node_str) return node_str node2str(root) return duplicated_nodes # Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class SolutionCount: def findDuplicateSubtrees(self, root: TreeNode) -> List[TreeNode]: # node_str -> count node_str_count = defaultdict(int) duplicated_nodes = list() def node2str(node): """ this function accomplishes two tasks: - index each node into a string - search the duplicated nodes during the traversal """ nonlocal node_str_count nonlocal duplicated_nodes if node is None: return "" node_str = "{}({})({})".format( node.val, node2str(node.left), node2str(node.right)) node_str_count[node_str] += 1 if node_str_count[node_str] == 2: duplicated_nodes.append(node) return node_str node2str(root) return duplicated_nodes

[ "lisong.guo@me.com" ]

lisong.guo@me.com

15fd9952fee0476a4522d0e9c5220985962185cf

88abc8645e499a61e96e2979ae6092e98bfd09e7

/streamz/utils.py

4e1538da7c4506a9bf7fed145c07d2eb9fdde2bc

[ "BSD-3-Clause" ]

permissive

vishalbelsare/streamz

5e2d6e112b6a2a90e396c4e3bc11cb1167d879e3

b73a8c4c5be35ff1dae220daaefbfd2bfa58e0a1

refs/heads/master

2022-12-24T17:28:40.600327

2022-11-22T16:40:35

207,001,623

0

BSD-3-Clause

2022-12-10T04:20:03

2019-09-07T17:20:32

Python

UTF-8

Python

false

1,184

py

_method_cache = {} class methodcaller(object): """ Return a callable object that calls the given method on its operand. Unlike the builtin `operator.methodcaller`, instances of this class are serializable """ __slots__ = ('method',) func = property(lambda self: self.method) # For `funcname` to work def __new__(cls, method): if method in _method_cache: return _method_cache[method] self = object.__new__(cls) self.method = method _method_cache[method] = self return self def __call__(self, obj, *args, **kwargs): return getattr(obj, self.method)(*args, **kwargs) def __reduce__(self): return (methodcaller, (self.method,)) def __str__(self): return "<%s: %s>" % (self.__class__.__name__, self.method) __repr__ = __str__ class MethodCache(object): """Attribute access on this object returns a methodcaller for that attribute. Examples -------- >>> a = [1, 3, 3] >>> M.count(a, 3) == a.count(3) True """ __getattr__ = staticmethod(methodcaller) __dir__ = lambda self: list(_method_cache) M = MethodCache()

[ "noreply@github.com" ]

vishalbelsare.noreply@github.com

3a084bb437dc7e9fbb08e486b1cc9993909d21bb

71d535545c4f3b2fc626cd04cfcee22805b67353

/copacity_app/migrations/0007_auto_20210613_1019.py

c0f52b9073d682a55e6c58ee766848aa894fabd7

[]

no_license

mcnalj/copacity_django

01a018d32ee9cb9ba392e5dcd160d636ba0b5b74

48432cff7585af342599c06cac497947e4b68195

refs/heads/master

2023-07-04T14:27:50.736252

2021-08-10T16:53:59

383,779,070

0

null

UTF-8

Python

false

1,768

py

# Generated by Django 3.1.7 on 2021-06-13 10:19 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('copacity_app', '0006_checkin_owner'), ] operations = [ migrations.CreateModel( name='Circle', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=50)), ('createdBy', models.CharField(max_length=50)), ('createdOn', models.DateTimeField(auto_now_add=True)), ('adminId', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='CircleMembership', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('circle', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='copacity_app.circle')), ('inviter', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='circle_invites', to=settings.AUTH_USER_MODEL)), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), migrations.AddField( model_name='circle', name='members', field=models.ManyToManyField(related_name='circle_member', through='copacity_app.CircleMembership', to=settings.AUTH_USER_MODEL), ), ]

[ "example@example.com" ]

example@example.com

ef954e4bc9bcc4a0ca428034f6427da6e1577c8f

07da31b260bf2949ffd9463ad4f777ca93b75d43

/sleekforum/src/sleekapps/threads/views/post/post.py

6f81800803801b5318b4dba53439f620da360d57

[]

no_license

adepeter/sleek-docker

134fd7de12ade8c521ceb8e1b2b2611fa2224dde

dcf010c3da53093600101d970c6888c82360209f

refs/heads/master

2022-12-15T14:53:01.499098

2020-09-14T00:42:31

282,499,689

0

null

2020-07-31T14:31:22

2020-07-25T18:12:19

JavaScript

UTF-8

Python

false

1,459

py

from django.contrib import messages from django.views.generic.edit import CreateView, DeleteView, UpdateView from django.utils.translation import gettext_lazy as _ from ...forms.post.post import PostEditForm, PostForm from ...viewmixins.post import BasePostMixin TEMPLATE_URL = 'threads/post' class EditPost(BasePostMixin, UpdateView): form_class = PostEditForm template_name = f'{TEMPLATE_URL}/edit_post.html' def get_form_kwargs(self): kwargs = super().get_form_kwargs() kwargs.update({'request': self.request}) return kwargs def form_valid(self, form): if not form.has_changed(): messages.success(self.request, _('No changes were made to your reply')) else: messages.success(self.request, _('Post was successfully edited.')) return super().form_valid(form) class DeletePost(BasePostMixin, DeleteView): pass class ReplyPost(BasePostMixin, CreateView): form_class = PostForm template_name = f'{TEMPLATE_URL}/reply_post.html' def get_context_data(self, **kwargs): context = super().get_context_data(**kwargs) context['parent'] = self.get_object() return context def form_valid(self, form): parent_object = self.get_object() form.instance.thread = parent_object.thread form.instance.parent = parent_object form.instance.user = self.request.user return super().form_valid(form)

[ "adepeter26@gmail.com" ]

adepeter26@gmail.com

418ff5b81b82739dbb020083e568e2276627c16e

fdaba69f8d3ae3e645cb548a31111814b67f88bc

/credit/xgboost_Chunk_join.py

3d222a1d0c5720a80dc1aa63bfc2f49b7910ada3

[]

no_license

curryli/pandasFlow

6c381a06843f353f3449666cc9aee3e3fc2c3620

891963e1d9acd8cdd23732180a3fd4b4633bc335

refs/heads/master

2020-12-07T15:24:36.500075

2018-07-01T09:01:09

95,520,789

4

3

null

UTF-8

Python

false

4,752

py

# -*- coding: utf-8 -*- import pandas as pd from sklearn.cross_validation import train_test_split from sklearn.metrics import recall_score, precision_score from sklearn.metrics import precision_recall_fscore_support from sklearn.linear_model import LogisticRegression from sklearn.metrics import confusion_matrix from sklearn.utils import shuffle import datetime from collections import Counter from xgboost.sklearn import XGBClassifier import numpy as np start_time = datetime.datetime.now() ################################################# #reader = pd.read_csv("new_FE_idx.csv", low_memory=False, iterator=True) #reader = pd.read_csv("trans_small.csv", low_memory=False, iterator=True) reader = pd.read_csv("cert_all_right.csv", low_memory=False, iterator=True) loop = True chunkSize = 100000 chunks = [] i = 0 while loop: try: chunk = reader.get_chunk(chunkSize) chunks.append(chunk) if (i%5)==0: print i i = i+1 except StopIteration: loop = False print "Iteration is stopped." df_All = pd.concat(chunks, ignore_index=True) print df_All.columns #df_All = df_All.drop(["Trans_at","hist_fraud_cnt"], axis=1,inplace=False) df_All = df_All[(df_All["label"] == 0) | (df_All["label"] == 1)] df_All_stat = pd.read_csv("train_1108.csv", sep=',') df_All_stat = df_All_stat[(df_All_stat["label"]==0) | (df_All_stat["label"]==1)] df_All_stat= df_All_stat.drop( ["label"], axis=1,inplace=False) df_All = pd.merge(left=df_All, right=df_All_stat, how='left', left_on='certid', right_on='certid') df_All = shuffle(df_All) df_All = df_All.fillna(-1) df_X = df_All.drop(["label","certid","card_no"], axis=1,inplace=False) df_y = df_All[["certid","label"]] X_train, X_test, y_train, y_test = train_test_split(df_X, df_y, test_size=0.2) np.savetxt("X_train_cols.csv",np.array(X_train.columns),fmt="%s" ) ############################################### certid_test = y_test y_train = y_train.drop(["certid"], axis=1,inplace=False) y_test = y_test.drop(["certid"], axis=1,inplace=False) clf = XGBClassifier(learning_rate =0.1,n_estimators=500,max_depth=5,gamma=0.05,subsample=0.8,colsample_bytree=0.8,objective= 'binary:logistic', reg_lambda=1,seed=27) print "start training" clf.fit(X_train, y_train) pred = clf.predict(X_test) cm1=confusion_matrix(y_test,pred) print cm1 print "For Trans:\n" result = precision_recall_fscore_support(y_test,pred) #print result precision_0 = result[0][0] recall_0 = result[1][0] f1_0 = result[2][0] precision_1 = result[0][1] recall_1 = result[1][1] f1_1 = result[2][1] print "precision_0: ", precision_0," recall_0: ", recall_0, " f1_0: ", f1_0 #print "certid_test_ori\n",certid_test certid_test.index = range(certid_test.shape[0]) #print "certid_test\n",certid_test certid_pred = pd.DataFrame(pred,columns=["pred"]) #print "certid_pred\n", certid_pred certid_DF = pd.concat([certid_test,certid_pred], axis=1, ignore_index=True) certid_DF.columns = ["certid","label","pred"] #print "certid_DF\n",certid_DF print certid_DF.dtypes certid_DF.to_csv("certid_DF_drop.csv") certid_grouped = certid_DF.groupby([certid_DF['certid']]) #certid_grouped = certid_DF.groupby([certid_DF['certid']], as_index=False) # def label_cnt(arr): # 同一个人出现次数最多的元素 # cnt_set = Counter(arr) # max_cnt_pair = cnt_set.most_common(1)[0] # (maxitem,maxcount) # return max_cnt_pair[0] def label_cnt(arr): # 同一个人出现次数最多的元素 cnt_0 = 0 arr_values = arr.values for i in range(len(arr_values)): if arr_values[i]==float(0): cnt_0 = cnt_0+1 if(cnt_0>0): return 0 else: return 1 agg_dict = {} agg_dict["pred"] = [label_cnt] agg_stat_df = certid_grouped.agg(agg_dict) agg_stat_df.columns = agg_stat_df.columns.map('{0[0]}-{0[1]}'.format) #https://www.cnblogs.com/hhh5460/p/7067928.html agg_stat_df.reset_index(level=0, inplace=True) #print agg_stat_df pred_label_DF = agg_stat_df[["certid", "pred-label_cnt"]] true_label_DF = certid_test.drop_duplicates() compare_df = pd.merge(left=true_label_DF, right=pred_label_DF, how='left', left_on='certid', right_on='certid') y_test = compare_df["label"] pred = compare_df["pred-label_cnt"] cm2=confusion_matrix(y_test,pred) print cm2 print "For Person:\n" result = precision_recall_fscore_support(y_test,pred) #print result precision_0 = result[0][0] recall_0 = result[1][0] f1_0 = result[2][0] precision_1 = result[0][1] recall_1 = result[1][1] f1_1 = result[2][1] print "precision_0: ", precision_0," recall_0: ", recall_0, " f1_0: ", f1_0 end_time = datetime.datetime.now() delta_time = str((end_time-start_time).total_seconds()) print "cost time",delta_time,"s"

[ "xurui.lee@msn.com" ]

xurui.lee@msn.com

4b3187694d3f43ef8b7ee834c64e18fad6e4b5d3

2290eed5c494202beea0da1b9257a38b7a4403d2

/script/[662]二叉树最大宽度.py

382e8af49c05465745fefb5b155a1be322b7d57b

[]

no_license

DSXiangLi/Leetcode_python

4b1c9848ea774955fb252b9bd796ba8d46ad728e

a2ef0ba5e86405dbf68dbc1ffeb086c7d864db1d

refs/heads/main

2022-09-01T04:34:04.260402

2022-08-20T01:12:27

445,347,891

1

0

null

2022-07-23T06:32:14

2022-01-07T00:15:20

Python

UTF-8

Python

false

2,352

py

# 给定一个二叉树，编写一个函数来获取这个树的最大宽度。树的宽度是所有层中的最大宽度。这个二叉树与满二叉树（full binary tree）结构相同，但一些节 # 点为空。 # # 每一层的宽度被定义为两个端点（该层最左和最右的非空节点，两端点间的null节点也计入长度）之间的长度。 # # 示例 1: # # # 输入: # # 1 # / \ # 3 2 # / \ \ # 5 3 9 # # 输出: 4 # 解释: 最大值出现在树的第 3 层，宽度为 4 (5,3,null,9)。 # # # 示例 2: # # # 输入: # # 1 # / # 3 # / \ # 5 3 # # 输出: 2 # 解释: 最大值出现在树的第 3 层，宽度为 2 (5,3)。 # # # 示例 3: # # # 输入: # # 1 # / \ # 3 2 # / # 5 # # 输出: 2 # 解释: 最大值出现在树的第 2 层，宽度为 2 (3,2)。 # # # 示例 4: # # # 输入: # # 1 # / \ # 3 2 # / \ # 5 9 # / \ # 6 7 # 输出: 8 # 解释: 最大值出现在树的第 4 层，宽度为 8 (6,null,null,null,null,null,null,7)。 # # # 注意: 答案在32位有符号整数的表示范围内。 # Related Topics 树深度优先搜索广度优先搜索二叉树 👍 384 👎 0 # leetcode submit region begin(Prohibit modification and deletion) # Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class Solution: def widthOfBinaryTree(self, root: Optional[TreeNode]) -> int: maxw = 0 stack = [(root,0)] while stack: l = len(stack) left = 0 for i in range(l): node, pos = stack.pop(0) if i==0: left= pos if node.left: stack.append((node.left, pos*2)) if node.right: stack.append((node.right, pos*2+1)) if i==l-1: maxw = max(maxw, pos-left+1) return maxw # leetcode submit region end(Prohibit modification and deletion)

[ "liningrui@xiaohongshu.com" ]

liningrui@xiaohongshu.com

68a8b7bca0c433c9063cdb4726ee5fc8ce83c752

48aacf0425c5ab071972034c3fbd388feb036578

/node-7/site-packages/ceph_deploy/connection.py

381f6afa4c9bd0454eb2cda6a9881067950e2c18

[]

no_license

wputra/MOS-centos

2b8ec0116bb3a28632c54d6052d322a42391439f

0a4f24dd4183d4d44e8c7beb27adce12e42f0201

refs/heads/master

2021-01-10T19:22:22.920342

2014-09-12T03:33:54

null

0

null

UTF-8

Python

false

654

py

from ceph_deploy.lib.remoto import Connection from sudo_pushy import needs_sudo # TODO move this to utils once pushy is out def get_connection(hostname, logger, threads=5): """ A very simple helper, meant to return a connection that will know about the need to use sudo. """ try: return Connection( hostname, logger=logger, sudo=needs_sudo(), threads=threads, ) except Exception as error: msg = "connecting to host: %s " % hostname errors = "resulted in errors: %s %s" % (error.__class__.__name__, error) raise RuntimeError(msg + errors)

[ "wasis.putra@gmail.com" ]

wasis.putra@gmail.com

f54066fc82d29ccbcbb0f6fbc82e0b625fe67fb5

ad0857eaba945c75e705594a53c40dbdd40467fe

/leetCode/maximal_rectangle.py

98b030c3831e8cf2db830fb6e04f0209fe45fc5d

[ "MIT" ]

permissive

yskang/AlgorithmPractice

c9964d463fbd0d61edce5ba8b45767785b0b5e17

3efa96710e97c8740d6fef69e4afe7a23bfca05f

refs/heads/master

2023-05-25T13:51:11.165687

2023-05-19T07:42:56

67,045,852

0

null

2021-06-20T02:42:27

2016-08-31T14:40:10

Python

UTF-8

Python

false

927

py

class Solution(object): def maximal_rectangle(self, matrix): if not matrix or not matrix[0]: return 0 width = len(matrix[0]) heights = [0] * (width+1) ans = 0 for row in matrix: for i in range(width): heights[i] = heights[i] + 1 if row[i] == '1' else 0 stack = [-1] for i in range(width+1): while heights[i] < heights[stack[-1]]: h = heights[stack.pop()] w = i - 1 - stack[-1] ans = max(ans, h * w) stack.append(i) return ans if __name__ == "__main__": sol = Solution() print(sol.maximal_rectangle([["1", "0", "1", "0", "0"], ["1", "0", "1", "1", "1"], ["1", "1", "1", "1", "1"], ["1", "0", "1", "1", "0"]]))

[ "yongsung.kang@gmail.com" ]

yongsung.kang@gmail.com

ac7a8bc1157a39c61201db61f88be40f9b180771

7cf52b987da6595ebc5f763b384b03e608ccb25f

/tests/index/test_mongodb_index.py

87a66da4180d9cc8e832f22eb992d389b7dee1c3

[]

no_license

shaypal5/dinglebop

93fdfda48ec4d91c0a9485173a106d1edbcd1b29

a10473b4abecfd70a00cd9086aa8919a404959c9

refs/heads/master

2021-08-20T10:17:46.640046

2017-11-14T18:01:43

109,569,728

0

null

UTF-8

Python

false

3,710

py

"""Testing the implementation of MongoDB-based dingle indexes.""" import pytest from dinglebop.index.mongodb import MongoDBIndex from dinglebop.shared import get_dinglebop_cfg SAMPLE_IDEN1 = 'school_data_2016' SAMPLE_IDEN2 = 'school_data_2017' SAMPLE_DOC1 = {'identifier': SAMPLE_IDEN1, 'version': 'v1.0', 'store': 'somestore', 'format_identifier': 'arrow'} SAMPLE_DOC2 = {'identifier': SAMPLE_IDEN1, 'version': 'v1.1', 'store': 'somestore', 'format_identifier': 'csv'} SAMPLE_DOC3 = {'identifier': SAMPLE_IDEN2, 'version': 'v0.03', 'store': 'somestore', 'format_identifier': 'csv'} SAMPLE_DOC4 = {'identifier': SAMPLE_IDEN2, 'version': 'v0.23', 'store': 'somestore', 'format_identifier': 'csv'} SAMPLE_DOCS = [SAMPLE_DOC1, SAMPLE_DOC2, SAMPLE_DOC3, SAMPLE_DOC4] def _get_mongodb_idx_instance(): dcfg = get_dinglebop_cfg() idx_cfg = dcfg['dingles']['dinglebop_test']['index'].copy() assert idx_cfg.pop('type') == 'MongoDB' return MongoDBIndex(**idx_cfg) def _get_idx_collection(): return _get_mongodb_idx_instance()._get_collection() @pytest.fixture(scope="session", autouse=True) def reset_idx_collection(): idx_obj = _get_mongodb_idx_instance() collection = idx_obj._get_collection() if MongoDBIndex._INDEX_NAME in collection.index_information(): collection.drop_index(MongoDBIndex._INDEX_NAME) collection.delete_many({}) collection.insert_many([d.copy() for d in SAMPLE_DOCS]) def test_mongodb_index_autocreation(): idx_collection = _get_idx_collection() assert MongoDBIndex._INDEX_NAME in idx_collection.index_information() def test_get_all_dataset_entries(): dingle_idx = _get_mongodb_idx_instance() cursor = dingle_idx.get_all_dataset_entries(identifier=SAMPLE_IDEN1) docs = list(cursor) assert len(docs) == 2 assert docs[0]['version'] == 'v1.1' assert docs[1]['version'] == 'v1.0' def test_get_latest_dataset_entry(): dingle_idx = _get_mongodb_idx_instance() doc1 = dingle_idx.get_latest_dataset_entry(identifier=SAMPLE_IDEN1) assert doc1['version'] == 'v1.1' doc2 = dingle_idx.get_latest_dataset_entry(identifier=SAMPLE_IDEN2) assert doc2['version'] == 'v0.23' def test_get_dataset_entry_by_version(): dingle_idx = _get_mongodb_idx_instance() doc = dingle_idx.get_dataset_entry_by_version( identifier=SAMPLE_IDEN1, version='v1.0') assert doc['format_identifier'] == 'arrow' @pytest.fixture(scope='function') def clear_all_idx_docs(): collection = _get_idx_collection() collection.delete_many({}) def test_add_entry(clear_all_idx_docs): dingle_idx = _get_mongodb_idx_instance() dingle_idx.add_entry(**SAMPLE_DOC1) dingle_idx.add_entry(**SAMPLE_DOC2) docs = list(dingle_idx.get_all_dataset_entries(identifier=SAMPLE_IDEN1)) assert len(docs) == 2 @pytest.fixture(scope='function') def add_all_idx_docs(): collection = _get_idx_collection() collection.delete_many({}) collection.insert_many([d.copy() for d in SAMPLE_DOCS]) def test_remove_entries(add_all_idx_docs): dingle_idx = _get_mongodb_idx_instance() docs1 = list(dingle_idx.get_all_dataset_entries(identifier=SAMPLE_IDEN1)) assert len(docs1) == 2 docs2 = list(dingle_idx.get_all_dataset_entries(identifier=SAMPLE_IDEN2)) assert len(docs2) == 2 dingle_idx.remove_entries(identifier=SAMPLE_IDEN1, version='v1.0') docs1 = list(dingle_idx.get_all_dataset_entries(identifier=SAMPLE_IDEN1)) assert len(docs1) == 1 dingle_idx.remove_entries(identifier=SAMPLE_IDEN2) docs2 = list(dingle_idx.get_all_dataset_entries(identifier=SAMPLE_IDEN2)) assert len(docs2) == 0

[ "shaypal5@gmail.com" ]

shaypal5@gmail.com

634e12c0e89842b519a5bae4fcff0bcc9f6bc466

6e19835f99efea46d7b7966144efa8e2302d5e4c

/tensorflow/python/autograph/utils/misc_test.py

c813e0f5c96386a0d0fbd078bd5b663c688b0327

[ "Apache-2.0" ]

permissive

Cincan/tensorflow

415fba147ef4676901f424a839d751aa7d1c50f0

94c9acddd9f3fd73a5e4b5bc1fd7c9284a68ea75

refs/heads/master

2020-04-08T14:07:14.355697

2018-11-28T00:59:40

159,422,705

1

0

Apache-2.0

2018-11-28T01:08:35

null

UTF-8

Python

false

1,719

py

# Copyright 2017 The TensorFlow Authors. 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. # ============================================================================== """Tests for misc module.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow.python.autograph.utils.misc import alias_tensors from tensorflow.python.framework.constant_op import constant from tensorflow.python.ops.variables import Variable from tensorflow.python.platform import test class MiscTest(test.TestCase): def test_alias_single_tensor(self): a = constant(1) new_a = alias_tensors(a) self.assertFalse(new_a is a) with self.cached_session() as sess: self.assertEqual(1, self.evaluate(new_a)) def test_alias_tensors(self): a = constant(1) v = Variable(2) s = 'a' l = [1, 2, 3] new_a, new_v, new_s, new_l = alias_tensors(a, v, s, l) self.assertFalse(new_a is a) self.assertTrue(new_v is v) self.assertTrue(new_s is s) self.assertTrue(new_l is l) with self.cached_session() as sess: self.assertEqual(1, self.evaluate(new_a)) if __name__ == '__main__': test.main()

[ "gardener@tensorflow.org" ]

gardener@tensorflow.org

d3bb18f8490dbe42f2945f71dc53ab3f6ba81073

012aadc12dc2a4560eabc04527414c3883e87e3d

/myvenv/bin/autopep8

b7dcecda5a6c5b3d815b73491659a8d14741a669

[]

no_license

kosiannpann/my-first-blog

a0c17286256e0d16a90b40b6b2f9beddebe9b03e

e41f4966da20785cabb9402e02a4119fb981fee1

refs/heads/master

2023-06-09T04:19:02.276691

2021-07-04T02:52:22

376,177,938

0

null

UTF-8

Python

false

237

#!/Users/ootadaiki/djangogirls/myvenv/bin/python # -*- coding: utf-8 -*- import re import sys from autopep8 import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "you@example.com" ]

you@example.com

a1169142ea4526aa901d36823d53da96429542b2

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p02898/s602471427.py

314d28278090b7657613ada6c2c07aa32f78faee

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

528

py

from sys import stdin import sys import math from functools import reduce import functools import itertools from collections import deque,Counter,defaultdict from operator import mul import copy # ! /usr/bin/env python # -*- coding: utf-8 -*- import heapq sys.setrecursionlimit(10**6) # INF = float("inf") INF = 10**18 import bisect import statistics mod = 10**9+7 # mod = 998244353 N, K = map(int, input().split()) h = list(map(int, input().split())) ans = 0 for i in range(N): if h[i] >= K: ans += 1 print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

df7b698115c3ffbcc37de296d1f45a03dd270d4e

78144baee82268a550400bbdb8c68de524adc68f

/Production/python/Autumn18/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8_cff.py

76c72b7101248b1ce6344a581378b039f338ce9b

[]

no_license

tklijnsma/TreeMaker

e6989c03189b849aff2007bad22e2bfc6922a244

248f2c04cc690ef2e2202b452d6f52837c4c08e5

refs/heads/Run2_2017

2023-05-26T23:03:42.512963

2020-05-12T18:44:15

263,960,056

1

2

null

2020-09-25T00:27:35

2020-05-14T15:57:20

null

UTF-8

Python

false

1,467

py

import FWCore.ParameterSet.Config as cms maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) ) readFiles = cms.untracked.vstring() secFiles = cms.untracked.vstring() source = cms.Source ("PoolSource",fileNames = readFiles, secondaryFileNames = secFiles) readFiles.extend( [ '/store/mc/RunIIAutumn18MiniAOD/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8/MINIAODSIM/102X_upgrade2018_realistic_v15-v2/30000/38EB0BD1-6F82-A44F-BF83-86E69D8B150E.root', '/store/mc/RunIIAutumn18MiniAOD/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8/MINIAODSIM/102X_upgrade2018_realistic_v15-v2/30000/3A2A6249-6A8F-D24F-A36F-4C441E9A6DF1.root', '/store/mc/RunIIAutumn18MiniAOD/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8/MINIAODSIM/102X_upgrade2018_realistic_v15-v2/30000/4041B441-D1EF-534F-B6BB-C2C07AB51940.root', '/store/mc/RunIIAutumn18MiniAOD/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8/MINIAODSIM/102X_upgrade2018_realistic_v15-v2/30000/795C52C1-CEAD-7F44-9D3B-8737D8AC54DE.root', '/store/mc/RunIIAutumn18MiniAOD/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8/MINIAODSIM/102X_upgrade2018_realistic_v15-v2/30000/BF2BF1E5-ECC7-9042-A2A8-B906E018E1F2.root', '/store/mc/RunIIAutumn18MiniAOD/RPV_2t6j_mStop-1300_mN1-100_TuneCP2_13TeV-madgraphMLM-pythia8/MINIAODSIM/102X_upgrade2018_realistic_v15-v2/30000/FBE70B20-508A-984A-9CBF-95601BA7E965.root', ] )

[ "Chris_Madrid@Baylor.edu" ]

Chris_Madrid@Baylor.edu

0bf8b725ddbfa47071048214793a8fd56f8a68d9

90c6262664d013d47e9a3a9194aa7a366d1cabc4

/tests/storage/cases/test_KT1GvgQwPwo8ZdYojFrQyjs1QtjRKjn52cbV.py

2ae9510b0d691b63af6e04ec0a6f9d672271926b

[ "MIT" ]

permissive

tqtezos/pytezos

3942fdab7aa7851e9ea81350fa360180229ec082

a4ac0b022d35d4c9f3062609d8ce09d584b5faa8

refs/heads/master

2021-07-10T12:24:24.069256

2020-04-04T12:46:24

227,664,211

1

0

MIT

2020-12-30T16:44:56

2019-12-12T17:47:53

Python

UTF-8

Python

false

1,130

py

from unittest import TestCase from tests import get_data from pytezos.michelson.converter import build_schema, decode_micheline, encode_micheline, micheline_to_michelson class StorageTestKT1GvgQwPwo8ZdYojFrQyjs1QtjRKjn52cbV(TestCase): @classmethod def setUpClass(cls): cls.maxDiff = None cls.contract = get_data('storage/zeronet/KT1GvgQwPwo8ZdYojFrQyjs1QtjRKjn52cbV.json') def test_storage_encoding_KT1GvgQwPwo8ZdYojFrQyjs1QtjRKjn52cbV(self): type_expr = self.contract['script']['code'][1] val_expr = self.contract['script']['storage'] schema = build_schema(type_expr) decoded = decode_micheline(val_expr, type_expr, schema) actual = encode_micheline(decoded, schema) self.assertEqual(val_expr, actual) def test_storage_schema_KT1GvgQwPwo8ZdYojFrQyjs1QtjRKjn52cbV(self): _ = build_schema(self.contract['script']['code'][0]) def test_storage_format_KT1GvgQwPwo8ZdYojFrQyjs1QtjRKjn52cbV(self): _ = micheline_to_michelson(self.contract['script']['code']) _ = micheline_to_michelson(self.contract['script']['storage'])

[ "mz@baking-bad.org" ]

mz@baking-bad.org

8f05bd2092972f6b401e756e15c2117a31a5a4ba

ad69b52951c2f80d152b9ce2225b9a588f110deb

/fan_element_struct.py

66a7720d1a15cb86b7b4a0c70052200350ac8318

[]

no_license

hailangzz/fan_health_program

47c70fe884ec8e28b20be63f99d5c3004bb2a261

137d8a1a2271a44c68fe5a5b2b4e367023c0efad

refs/heads/master

2020-03-19T16:03:13.442179

2018-06-09T07:47:34

136,698,139

0

1

null

UTF-8

Python

false

8,210

py

#coding=utf-8 import numpy as np import copy def fan_element_struct(): #机组状态码暂时不确定，因此后续动态添加···，做单台机组状态码频率分布···,'stames_alive_list'是不同机组状态的存活列表··· stames_code={'stamescode_number':0,'stamescode_time':0,'reduce_power':0,'stames_alive_list':[]} #机组故障及其次数统计 error={'uiHubErr':{'HubErr_code':{},'starttime':[]}, 'uiErrFir':{'ErrFir_code':{},'starttime':[]}, 'uiConErr':{'ConErr_code':{},'starttime':[]}, 'uiYawErr':{'YawErr_code':{},'starttime':[]}, 'uiWarFir':{'WarFir_code':{},'starttime':[]} } #windspeed_array=[set_wind_cut for set_wind_cut in np.arange(3,20,0.1)] #存储计算机组正常的功率曲线数据···,可以基于此数据，统计风况概率分布，不同风况下机组总发电量分布``` normal_power_curve={} windspeed_array=np.arange(3,20,0.2) for wind_cut in windspeed_array: if wind_cut not in normal_power_curve: normal_power_curve[round(wind_cut,1)]={'total_power':0,'registe_number':0,'poweravg':0} hzth_standard_wind_power={} hzth_power_list=[123,142,164,189,213,239,268,300,331,366,398,434,470,514,552,593,630,661,707,742,806,843,893,953,1001,1049,1095,1147,1204,1248,1293, 1353,1398,1428,1465,1481,1493,1501,1514,1528,1540,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552, 1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552,1552 ] windspeed_array=np.arange(3,20,0.2) for wind_cut_id in range(len(windspeed_array)): if windspeed_array[wind_cut_id] not in hzth_standard_wind_power: hzth_standard_wind_power[round(windspeed_array[wind_cut_id],1)]={'poweravg':0} hzth_standard_wind_power[round(windspeed_array[wind_cut_id],1)]['poweravg']=hzth_power_list[wind_cut_id] #用于存储风机全部出口功率频率分布··· power_status_distribute={} power_status=np.arange(0,1800,10) for power_cut in power_status: if power_cut not in power_status_distribute: power_status_distribute[power_cut]={'registe_number':0} #用于统计存储风机风况频率分布··· wind_status_distribute={} wind_array=np.arange(0,20,0.2) for wind_cut in wind_array: if wind_cut not in wind_status_distribute: wind_status_distribute[round(wind_cut,1)]={'registe_number':0} fChoGenTemAve_status_distribute={} temperature1_cut=np.arange(0,200,2) for temp1_cut in temperature1_cut: if temp1_cut not in fChoGenTemAve_status_distribute: fChoGenTemAve_status_distribute[temp1_cut]={'registe_number':0} fGeaBeaTemAve_status_distribute={} temperature1_cut=np.arange(0,150,2) for temp1_cut in temperature1_cut: if temp1_cut not in fGeaBeaTemAve_status_distribute: fGeaBeaTemAve_status_distribute[temp1_cut]={'registe_number':0} fGeaOilTemAve_status_distribute={} temperature1_cut=np.arange(0,150,2) for temp1_cut in temperature1_cut: if temp1_cut not in fGeaOilTemAve_status_distribute: fGeaOilTemAve_status_distribute[temp1_cut]={'registe_number':0} fGenTemAve_status_distribute={} temperature1_cut=np.arange(0,200,2) for temp1_cut in temperature1_cut: if temp1_cut not in fGenTemAve_status_distribute: fGenTemAve_status_distribute[temp1_cut]={'registe_number':0} fGenBeaDriTemAve_status_distribute={} temperature1_cut=np.arange(0,150,2) for temp1_cut in temperature1_cut: if temp1_cut not in fGenBeaDriTemAve_status_distribute: fGenBeaDriTemAve_status_distribute[temp1_cut]={'registe_number':0} fConGsclgbTemAve_status_distribute={} temperature1_cut=np.arange(0,150,2) for temp1_cut in temperature1_cut: if temp1_cut not in fConGsclgbTemAve_status_distribute: fConGsclgbTemAve_status_distribute[temp1_cut]={'registe_number':0} tenminlog={'wind_status_distribute':{},#存储风况频率分布 'power_status_distribute':{},#存储正常功率频率分布 'fChoGenTemAve_distribute':{},#存储机组发电机感应线圈温度频率分布··· 'fGeaBeaTemAve_distribute':{},#存储机组齿轮箱温度频率分布··· 'fGeaOilTemAve_distribute':{},#存储机组齿轮箱油温频率分布··· 'fGenTemAve_distribute':{}, 'fGenBeaDriTemAve_distribute':{}, 'fConGsclgbTemAve_distribute':{}, 'normal_power_splat':{'wind_list':[],'power_list':[]},#存储正常功率风速散点··· 'all_power_splat':{'wind_list':[],'power_list':[]},#存储所有功率风速散点··· 'selflimite_power_splat':{'wind_list':[],'power_list':[]},#存储超温限功率散点··· 'limite_power_splat':{'wind_list':[],'power_list':[]}, 'stop_power_splat':{'wind_list':[],'power_list':[]}, #超温限功率数据统计··· 'over_temperature':{'fChoGenTemAve':{'number':0,'total_time':0}, 'fGeaBeaTemAve':{'number':0,'total_time':0}, 'fGeaOilTemAve':{'number':0,'total_time':0}, 'fGenTemAve':{'number':0,'total_time':0}, 'fGenBeaDriTemAve':{'number':0,'total_time':0}, 'fConGsclgbTemAve':{'number':0,'total_time':0} }, 'totalpower':0,#机组总发电量··· 'normal_totalpower':0,#机组正常发电总的发电量存储··· 'selflimite_totaltime':0, 'limite_totaltime':0, 'stop_totaltime':0, 'over_temperature_totaltime':0, 'hzth_increase_totalpower':0, 'selflimite_reducepower':0, #限功率损失发电量统计··· 'limite_reducepower':0, 'stop_reducepower':0, 'fChoGenTemAve':{'registe_id':[],'temperature':[]}, 'fGeaBeaTemAve':{'registe_id':[],'temperature':[]}, 'fGeaOilTemAve':{'registe_id':[],'temperature':[]}, 'fGenTemAve':{'registe_id':[],'temperature':[]}, 'fGenBeaDriTemAve':{'registe_id':[],'temperature':[]}, 'fConGsclgbTemAve':{'registe_id':[],'temperature':[]} #机组部件温度数据概率分布统计··· } #初始化‘tenminlog’结构变量··· tenminlog['wind_status_distribute']=copy.deepcopy(wind_status_distribute) tenminlog['power_status_distribute']=copy.deepcopy(power_status_distribute) tenminlog['fChoGenTemAve_distribute']=copy.deepcopy(fChoGenTemAve_status_distribute) tenminlog['fGeaBeaTemAve_distribute']=copy.deepcopy(fGeaBeaTemAve_status_distribute) tenminlog['fGeaOilTemAve_distribute']=copy.deepcopy(fGeaOilTemAve_status_distribute) tenminlog['fGenTemAve_distribute']=copy.deepcopy(fGenTemAve_status_distribute) tenminlog['fGenBeaDriTemAve_distribute']=copy.deepcopy(fGenBeaDriTemAve_status_distribute) tenminlog['fConGsclgbTemAve_distribute']=copy.deepcopy(fConGsclgbTemAve_status_distribute) fan_element={'stames':{},'error':{},'tenminlog':{},'normal_power_curve':{},'fanset_information':{'fanid':0,'fanname':'','fanip':'','fantype':0,'plctype':0}} fan_element['error']=copy.deepcopy(error) fan_element['tenminlog']=copy.deepcopy(tenminlog) fan_element['normal_power_curve']=copy.deepcopy(normal_power_curve) fan_element['hzth_standard_wind_power']=copy.deepcopy(hzth_standard_wind_power) fan_root_dict={} return fan_root_dict,fan_element,stames_code

[ "344267342@qq.com" ]

344267342@qq.com

b7f51ac07e35b2adf6dab304ed1b86b064e9a447

29cc0a662b62078e553c461f05ef999c76c0f51f

/Lab_01/connection.py

7f6f22939e3081ad8120f3d5f4badfa55ace0957

[]

no_license

fefeagus/Redes_Sistemas_Distribuidos_2015

bd2978f439389d8f50cbe55a9681cede2530de26

eee77359891d6c52083c2bd116c2ae65cf36af14

refs/heads/master

2023-04-14T13:46:13.935385

2017-09-12T03:37:50

null

0

null

UTF-8

Python

false

7,300

py

# encoding: utf-8 # Copyright 2014 Carlos Bederián # $Id: connection.py 455 2011-05-01 00:32:09Z carlos $ import os import socket from constants import * import server class Connection(object): """ Conexión punto a punto entre el servidor y un cliente. Se encarga de satisfacer los pedidos del cliente hasta que termina la conexión. """ def __init__(self, socket, directory): # Inicialización de conexión self.sock = socket self.dir = directory self.buff_in = '' self.buff_out = '' self.connection_active = True def es_nombre_valido(self, name_file): """ Devuelve True si el nombre ingresado contiene caracteres validos o False en caso contrario. """ nombre = set(name_file) - VALID_CHARS return nombre == set([]) def send_buffer(self): """ Envia datos para ser recibidos por el cliente. """ while self.buff_out: cant_bytes = self.sock.send(self.buff_out) assert cant_bytes > 0 self.buff_out = self.buff_out[cant_bytes:] def unknown_command(self): """ Mensaje de comando inválido. """ self.buff_out += str(INVALID_COMMAND) self.buff_out += space + error_messages[INVALID_COMMAND] + EOL self.send_buffer() def wrong_arg_q(self): """ Mensaje de argumentos inválidos. """ self.buff_out += str(INVALID_ARGUMENTS) self.buff_out += space + error_messages[INVALID_ARGUMENTS] + EOL self.send_buffer() def file_not_found(self): """ Mensaje de archivo inexistente. """ self.buff_out += str(FILE_NOT_FOUND) self.buff_out += space + error_messages[FILE_NOT_FOUND] + EOL self.send_buffer() def bad_offset(self): """ Mensaje de posicion inexistente en un archivo. """ self.buff_out += str(BAD_OFFSET) self.buff_out += space + error_messages[BAD_OFFSET] + EOL self.send_buffer() def bad_eol(self): """ Mensaje de que se encontro un caracter r\n fuera de un terminador de pedido EOL. """ self.buff_out += str(BAD_EOL) self.buff_out += space + error_messages[BAD_EOL] + EOL self.send_buffer() def get_file_listing(self): """ Lista los archivos de un directorio. """ try: lista = os.listdir(self.dir) except: print('INTERNAL SERVER ERROR') raise INTERNAL_ERROR else: self.buff_out += "0 OK" + EOL for x in lista: self.buff_out += x self.buff_out += EOL self.buff_out += EOL self.send_buffer() def get_metadata(self, name_file): """ Devuelve el tamaño del archivo dado (en bytes). """ is_valid_name = self.es_nombre_valido(name_file) file_exist = os.path.isfile(os.path.join(self.dir, name_file)) if not is_valid_name: # si el nombre de archivo es valido self.wrong_arg_q() elif not file_exist: self.file_not_found() # Error interno del servidor else: try: data = os.path.getsize(os.path.join(self.dir, name_file)) except: print('INTERNAL SERVER ERROR') raise INTERNAL_ERROR else: self.buff_out += "0 OK" + EOL + str(data) + EOL self.send_buffer() def get_slice(self, avl_file, offset, size): """ Leer y muestra los datos del archivo ingresado desde el OFFSET hasta OFFSET + SIZE. """ file_exist = os.path.isfile(os.path.join(self.dir, avl_file)) if not file_exist: self.file_not_found() else: try: offset2 = int(offset) size2 = int(size) except ValueError: self.wrong_arg_q() else: size_file = size2 start_read = offset2 len_file = os.path.getsize(os.path.join(self.dir, avl_file)) offset_plus = start_read > len_file size_plus = (start_read + size_file) > len_file if offset_plus or size_plus: self.bad_offset() else: try: file_open = open(os.path.join(self.dir, avl_file), 'r') except IOError: print("el archivo no se pudo abrir") raise INTERNAL_ERROR file_open.seek(start_read) self.buff_out += "0 OK" + EOL remain = size_file while remain > 0: last_part = min(remain, SIZE_READ) bytes_read = file_open.read(last_part) self.buff_out += str(len(bytes_read)) self.buff_out += space + bytes_read + EOL remain -= len(bytes_read) self.send_buffer() self.buff_out += "0 " + EOL self.send_buffer() def quit(self): """ Cierra la conexion al cliente. """ self.buff_out += str(CODE_OK) + " Listo!" + EOL self.send_buffer() self.sock.close() self.connection_active = False def analizar(self, command): """ Analiza si el pedido esta bien escrito y si contiene la cantidad de argumentos necesarios para cada método. """ c_tmp = command.split(space) if c_tmp[0] == 'get_file_listing': if len(c_tmp) == 1: self.get_file_listing() else: self.wrong_arg_q() elif c_tmp[0] == 'get_metadata': if len(c_tmp) != 2 or c_tmp[1] == '': self.wrong_arg_q() else: self.get_metadata(c_tmp[1]) elif c_tmp[0] == 'get_slice': if len(c_tmp) == 4: self.get_slice(c_tmp[1], c_tmp[2], c_tmp[3]) else: self.wrong_arg_q() elif c_tmp[0] == 'quit': if len(c_tmp) == 1: self.quit() else: self.wrong_arg_q() else: self.unknown_command() def handle(self): """ Atiende eventos de la conexión hasta que termina. """ # Maneja recepciones y envíos hasta desconexión while self.connection_active: # Recibe datos hasta recibir un EOL while EOL not in self.buff_in: rec = self.sock.recv(SIZE_READ) self.buff_in += rec # Separa el primer "pedido" del resto request, self.buff_in = self.buff_in.split(EOL, 1) # Se fija que no exista error tipo 100 if new_line in request: self.bad_eol() # Analiza el primer "pedido" recibido else: self.analizar(request) # Cerramos el socket en desconexión self.sock.close()

[ "ferreyramario7@gmail.com" ]

ferreyramario7@gmail.com

20413f0c344df7cbdad1bb7338a11aa39fc9861d

48460db1a6fdc6c09845c86cf5fa257f1a32f08a

/leetcode/medium/0949_Largest_Time_for_Given_Digits.py

0a85a9dd6fad4107f8c6a0e5a7d7bc8004502a85

[]

no_license

MichalBrzozowski91/algorithms

9d0b085621ed94b1aff5473663fbdc686463cd8d

ae57535b574a800c6300eae7d55b21f2432c3baa

refs/heads/master

2022-12-20T08:00:59.385002

2020-09-30T16:32:33

290,835,098

0

null

UTF-8

Python

false

1,053

py

class Solution: def largestTimeFromDigits(self, A: List[int]) -> str: B = A.copy() for firstDigitLimit in [2,1]: A = B.copy() result = '' temp = [a for a in A if a in range(firstDigitLimit + 1)] if not temp: return '' dig = max(temp) result += str(dig) A.remove(dig) # Second digit if dig == 2: temp = [a for a in A if a in [0,1,2,3]] else: temp = A if not temp: continue dig = max(temp) result += str(dig) A.remove(dig) # Third digit temp = [a for a in A if a in [0,1,2,3,4,5]] if not temp: continue dig = max(temp) result += ':' + str(dig) A.remove(dig) # Fourth digit dig = A[0] result += str(dig) return result return ''

[ "noreply@github.com" ]

MichalBrzozowski91.noreply@github.com

172e43d93c0b543dc370d654dd22753e9dd1cdfd

f7574ee7a679261e758ba461cb5a5a364fdb0ed1

/MergeSortedArray.py

25c884f75350c4b5cb98ff52b73b35e165289aaa

[]

no_license

janewjy/Leetcode

807050548c0f45704f2f0f821a7fef40ffbda0ed

b4dccd3d1c59aa1e92f10ed5c4f7a3e1d08897d8

refs/heads/master

2021-01-10T19:20:22.858158

2016-02-26T16:03:19

40,615,255

1

0

null

UTF-8

Python

false

1,549

py

class Solution(object): def merge(self, nums1, m, nums2, n): """ :type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: void Do not return anything, modify nums1 in-place instead. """ i = 0 j = 0 for j in range(n): while i < m+j and nums1[i] < nums2[j]: i += 1 nums1.insert(i,nums2[j]) i += 1 nums1[m+j+1:] = nums2[j+1:] # inster() slow the code down def merge2(self, nums1, m, nums2, n): l1, l2, end = m-1, n-1, m+n-1 while l1 >= 0 and l2 >= 0: if nums1[l1] > nums2[l2]: nums1[end] = nums1[l1] l1 -= 1 else: nums1[end] = nums2[l2] l2 -= 1 end -= 1 if l1 < 0: nums1[:l2+1] = nums2[:l2+1] # 1-28 class Solution(object): def merge(self, nums1, m, nums2, n): """ :type nums1: List[int] :type m: int :type nums2: List[int] :type n: int :rtype: void Do not return anything, modify nums1 in-place instead. """ i,j,cur = m-1,n-1,m+n-1 while i>=0 and j>=0: if nums1[i] > nums2[j]: nums1[cur] = nums1[i] i-=1 else: nums1[cur] = nums2[j] j -= 1 cur -= 1 if i < 0: nums1[:cur+1] = nums2[:j+1]

[ "janewjy87@gmail.com" ]

janewjy87@gmail.com

74c5c8c7b320b2dfc6dc3ab53abcf9739fd64eaa

343bdaddfc66c6316e2cee490e9cedf150e3a5b7

/0001_0100/0076/0076.py

851fe3c3ab0a773579c4237f01aaebb9804a5a57

[]

no_license

dm-alexi/acmp

af7f6b4484b78f5922f3b464406a0ba5dea0d738

3fa0016d132adfeab7937b3e8c9687a34642c93a

refs/heads/master

2021-07-09T15:14:25.857086

2020-10-20T19:08:54

201,908,038

0

null

UTF-8

Python

false

584

py

def timeint(s): return int(s[:2]) * 60 + int(s[3:]) with open("input.txt", "r") as f, open("output.txt", "w") as q: m = 0 inlist, outlist = [], [] n = int(f.readline()) for i in range(n): a, b = (timeint(x) for x in f.readline().split()) inlist.append(a) outlist.append(b) inlist.sort() outlist.sort() i, j, c = 0, 0, 0 while i < n: if inlist[i] <= outlist[j]: i += 1 c += 1 if c > m: m = c else: j += 1 c -= 1 q.write(str(m))

[ "dm2.alexi@gmail.com" ]

dm2.alexi@gmail.com

24a2b2bd01037bb5984627af29d73e874afe85da

94ea21700381f12b72649a59d2c90ae32c7e04f0

/addons/hc_medication_administration/models/hc_res_medication_administration.py

43a24cc10010e8dd270762918187fcb536cf5171

[]

no_license

messakali/odoo-fhir

c07e2d058763580de2929d4c84ebd4717ac15c43

1f5c28a3fdd788370696a5f75ab68a2acfe16d25

refs/heads/master

2021-01-10T22:35:55.158494

2016-09-28T17:21:56

69,700,012

0

1

null

2016-09-30T20:30:57

2016-09-30T20:30:56

null

UTF-8

Python

false

450

py

# -*- coding: utf-8 -*- from openerp import models, fields, api # class hc_medication_administration(models.Model): # _name = 'hc_medication_administration.hc_medication_administration' # name = fields.Char() # value = fields.Integer() # value2 = fields.Float(compute="_value_pc", store=True) # description = fields.Text() # # @api.depends('value') # def _value_pc(self): # self.value2 = float(self.value) / 100

[ "lsison@moxylus.com" ]

lsison@moxylus.com

f3a1b7d5b8f3c6718af758c89fae01723081f4ca

ca0757ab59d6420efae766dae80a539a3b692fbd

/apps/ippcdrupal/auth_backends.py

ba28716f1c21d575cec5c18d2e1d8708a507320f

[]

no_license

hypertexthero/itwishlist

bc1cfe7f3542a395ab439ee5aa71c1991baaadff

148a085238ae86ee07255f94d3a48a92190ce5c5

refs/heads/master

2020-06-05T01:00:41.981168

2013-08-30T15:06:52

null

0

null

UTF-8

Python

false

8,052

py

# =todo: authenticate against drupal users db # Looks like we'll need to upgrade to Django 1.4... from django.conf import settings from django.contrib.auth import login from django.contrib.auth.models import User, check_password from itwishlist.apps.ippcdrupal.models import DrupalUsers # from itwishlist.apps.ippcdrupal.hashers import is_password_usable, get_hasher # =todo: upgrade to django 1.4 # from django.contrib.auth.hashers import is_password_usable, get_hasher from django.utils.encoding import smart_str # http://stackoverflow.com/questions/16482531/django-registration-custom-backend # class DrupalUserAuthBackend(object): # """ # Authenticates against django.contrib.auth.models.User. with my modifications # """ # supports_inactive_user = True # # """ # This function does not upgrade the user password hasher # """ # def check_password(self, password, encoded): # if not password or not is_password_usable(encoded): # # is_password_usable is only available in Django 1.4 # # https://docs.djangoproject.com/en/1.4/topics/auth/#django.contrib.auth.hashers.is_password_usable # # if not password: # return False # # password = smart_str(password) # encoded = smart_str(encoded) # # if encoded[0] == "$": # encoded = encoded[1:] # make it compatible so that drupal 7 sha512 hasher can work properly # # if len(encoded) == 32 and '$' not in encoded: # hasher = get_hasher('unsalted_md5') # else: # algorithm = encoded.split('$', 1)[0] # hasher = get_hasher(algorithm) # # is_correct = hasher.verify(password, encoded) # # return is_correct # # def authenticate(self, username=None, password=None, db=None, **kwargs): # try: # user = DrupalUsers.objects.using(db).get(name=username) # name in ippcdrupal.models.DrupalUsers # if self.check_password(password, user.pass_field): # return user # except DrupalUsers.DoesNotExist: # return None # # http://query7.com/django-authentication-backends # http://djangosnippets.org/snippets/2729/ # from account.models import Account # from itwishlist.apps.ippcdrupal.drupalhasher.DrupalPasswordHasher import verify # from django.contrib.auth.models import User # # class DrupalUserAuthBackend(object): # # def authenticate(self, username, password): # # try: # account = DrupalUsers.objects.using('drupaldb').get(username=username, sha_pass_hash=verify(username, password)) # # try: # user = User.objects.get(username=username) # # except User.DoesNotExist: # # user = User(username=account.username) # user.is_staff = False # user.is_superuser = False # user.set_unusable_password() # user.save() # # return user # # except Account.DoesNotExist: # # return None # # def get_user(self, id): # try: # return User.objects.get(id=id) # except User.DoesNotExist: # return None class DrupalUserAuthBackend: """ Authenticate against the settings ADMIN_LOGIN and ADMIN_PASSWORD. Use the login name, and a hash of the password. For example: ADMIN_LOGIN = 'admin' ADMIN_PASSWORD = 'sha1$4e987$afbcf42e21bd417fb71db8c66b321e9fc33051de' """ supports_object_permissions = False supports_anonymous_user = False supports_inactive_user = False def authenticate(self, username=None, password=None): # login_valid = (settings.ADMIN_LOGIN == username) # pwd_valid = check_password(password, settings.ADMIN_PASSWORD) # if login_valid and pwd_valid: try: user = DrupalUsers.objects.using('drupaldb').get(name=username) except DrupalUsers.DoesNotExist: # Create a new user. Note that we can set password # to anything, because it won't be checked; the password # from settings.py will. # user = User(username=username, password='test') # user.is_staff = False # user.is_active = False # user.is_superuser = False # user.save() return None # return None def get_user(self, user_id): try: return User.objects.get(pk=user_id) except User.DoesNotExist: return None # class DrupalUserAuthBackend(object): # """ # Authenticates against ippcdrupal.models.DrupalUsers # """ # # def authenticate(self, username=None, password=None, **kwargs): # # UserModel = get_user_model() # # if username is None: # # username = kwargs.get(UserModel.USERNAME_FIELD) # try: # user = DrupalUsers.objects.using('drupaldb').get(name=username) # name in ippcdrupal.models.DrupalUsers # # if check_password(password): # if check_password(password): # return user # except DrupalUsers.DoesNotExist: # return None # class SettingsBackend(object): # """ # Authenticate against the settings ADMIN_LOGIN and ADMIN_PASSWORD. # # Use the login name, and a hash of the password. For example: # # ADMIN_LOGIN = 'admin' # ADMIN_PASSWORD = 'sha1$4e987$afbcf42e21bd417fb71db8c66b321e9fc33051de' # """ # # def DrupalUserAuth(self, username=None, password=None, db=None, **kwargs): # login_valid = (settings.ADMIN_LOGIN == username) # pwd_valid = check_password(password, settings.ADMIN_PASSWORD) # if login_valid and pwd_valid: # try: # user = User.objects.using(db).get(username=name) # if user.check_password(password): # return user # # user = User.objects.get(username=username) # # except User.DoesNotExist: # # # Create a new user. Note that we can set password # # # to anything, because it won't be checked; the password # # # from settings.py will. # # user = User(username=username, password='get from settings.py') # # user.is_staff = True # # user.is_superuser = True # # user.save() # return user # return None # # def get_user(self, user_id): # try: # return User.objects.get(pk=user_id) # except User.DoesNotExist: # return None # # from __future__ import unicode_literals # from django.contrib.auth import get_user_model # from django.contrib.auth.models import Permission # # class DrupalUserAuth(object): # """ # Authenticates against django.contrib.auth.models.User. # """ # # def authenticate(self, username=None, password=None, db=None, **kwargs): # UserModel = get_user_model() # if username is None: # username = kwargs.get(UserModel.USERNAME_FIELD) # try: # user = UserModel.objects.using(db).get(username=username) # if user.check_password(password): # return user # except UserModel.DoesNotExist: # return None # from __future__ import unicode_literals # from django.contrib.auth import get_user_model # from django.contrib.auth.models import Permission # # class DrupalUserAuth(object): # """ # Authenticates against django.contrib.auth.models.User. # """ # # def authenticate(self, username=None, password=None, db=None, **kwargs): # UserModel = get_user_model() # if username is None: # username = kwargs.get(UserModel.USERNAME_FIELD) # try: # user = UserModel.objects.using(db).get(username=username) # if user.check_password(password): # return user # except UserModel.DoesNotExist: # return None # # #

[ "simon@hypertexthero.com" ]

simon@hypertexthero.com

b2e0397ffe57b93e5e6ae261bde6a10fee12cd3a

b213c8b10b831d5fdacfb65c145450f6af846a4f

/blog/blog.py

ce23082f7c014309cc37d87c9b6217fc56981450

[]

no_license

tuomas56/random-python-stuff

1df260532abeb0a3da02560ed23ad1ee1995f5b2

12737127a31f1a3b84456021e8a5ac81545324da

refs/heads/master

2020-12-31T04:42:12.123345

2015-11-25T21:54:28

46,889,061

0

null

UTF-8

Python

false

3,649

py

from bottle import server_names, ServerAdapter, run, request, Bottle, redirect,response, abort import markdown import re import os import pickle import uuid import scrypt import base64 from datetime import datetime, timedelta from cherrypy import wsgiserver from cherrypy.wsgiserver.ssl_builtin import BuiltinSSLAdapter from config import SSL_PRIV_KEY, PASS_DB, SALT_DB, HASH_TIME SCRIPT_RE = re.compile(r"\<script\>(.*?)\<\\script\>") HASH_TIME = timedelta.strptime("%H:%M:%S") InvalidUserPass = RuntimeError("Invalid username or password.") class SSLCherryPy(ServerAdapter): def run(self, handler): server = wsgiserver.CherryPyWSGIServer((self.host, self.port), handler) server.ssl_adapter = BuiltinSSLAdapter(SSL_PRIV_KEY, SSL_PRIV_KEY) try: server.start() finally: server.stop() server_names['sslcherrypy'] = SSLCherryPy def enable_cors(fn): def _enable_cors(*args, **kwargs): response.headers['Access-Control-Allow-Origin'] = '*' return fn(*args, **kwargs) return _enable_cors app = Bottle() current_hashes = {} with open(PASS_DB, "rb") as f: pass_db = pickle.load(f) with open(SALT_DB, "rb") as f: salt_db = pickle.load(f) class HashData: def __init__(self, hash, expiry, user): self.hash = hash self.expiry = expiry self.user = user def expired(self): return self.expiry < datetime.now() def authenticated(fn): def _authenticated(hash, *args, **kwargs): if hash in current_hashes: if not current_hashes[hash].expired(): return fn(current_hashes[hash], *args, **kwargs) else: del current_hashes[hash] redirect('/login/expired') else: redirect('/login/expired') return _authenticated def action_login(user, passwd): if user not in pass_db or pass_db[user] != passwd_hash(user, passwd): raise InvalidUserPass else: return generate_hash(user) def generate_hash(user): expiry = datetime.now() + HASH_TIME hash = uuid.uuid4() return Hash(hash, expiry, user) def generate_salt(): return base64.b64encode(os.urandom(16)).decode() def passwd_hash(user, passwd): return salt_db[user] + scrypt.hash(passwd, salt_db[user], mintime=0.1) @app.route("/do/login/<user>/<passwd>") @enable_cors def do_login(user, passwd): try: current_hashes[user] = action_login(user, passwd) redirect('/home/%s' % current_hashes[user]) except RuntimeError: redirect('/login/invalid') @app.route("/login/<error>") def login(error): return template('pages/login.html.tpl', error=login_error(error)) def login_error(error): if error = 'invalid': return 'Invalid username or password.' elif error = 'expired': return 'Hash has expired; please login.' elif error = 'none': return '' else: raise RuntimeError("No such login error.") class Article: def __init__(self, author, date_written, tags, text): self.author = author self.date_written = date_written self.tags = tags self.text = text class Comment: def __init__(self, author, date_posted, parent, article, text): self.author = author self.date_posted = date_posted self.parent = parent self.article = article self.text = text def process_article(text): lines = text.split("\n") author, date_written, tags, *lines = lines date_written = datetime.strptime(date_written, "%d/%m/%Y %H:%M") tags = tags.split(",") text = markdown.markdown('\n'.join(lines)) return Article(author, date_written, tags, text) def process_comment(author, date_posted, parent, article, text): return Comment(author, datetime.strptime(date_written, "%d/%m/%Y %H:%M"),article,SCRIPT_RE.replace(markdown.markdown(text), r"<code>\1</code>"))

[ "pigworts2@gmail.com" ]

pigworts2@gmail.com

b191a119c6debbe2643f12b03216b61002e09590

8f4c59e69cce2f6e932f55b3c65aae376b206a2c

/笨办法学python/ex47/skeleton/tests/ex47_tests.py

00d322ae6ea3a7f953674e7ad506bc4a1713fde2

[]

no_license

zmjm4/python

ef7206292f1c3a3a5763b25527024999de5e8e79

44cf74c0f16891c351ce214762218ccf2d7353a0

refs/heads/master

2020-05-27T17:23:48.776167

2018-05-24T07:14:16

null

0

null

UTF-8

Python

false

1,022

py

# -*- coding: utf-8 -*- from nose.tools import * from ex47.game import Room def test_room(): gold=Room("GoldRoom", """This room has gold in it you can grab. There's a door to the north.""") assert_equal(gold.name,"GoldRoom") assert_equal(gold.paths,{}) def test_room_paths(): center = Room("Center", "Test room in the center.") north = Room("North", "Test room in the north.") south = Room("South", "Test room in the south.") center.add_paths({'north':north,'south':south}) assert_equal(center.go('north'),north) assert_equal(center.go('south'),south) def test_map(): start = Room("Start", "You can go west and down a hole.") west = Room("Trees", "There are trees here, you can go east.") down = Room("Dungeon", "It's dark down here, you can go up.") start.add_paths({'west':west,'down':down}) west.add_paths({'east':start}) down.add_paths({'up':start}) assert_equal(start.go('west'),west) assert_equal(start.go('west').go('east'),start) assert_equal(start.go('down').go('up'),start)

[ "715073608@qq.com" ]

715073608@qq.com

58c46c9a110a1eb99789632d26ae3ae38b04e23d

9463d85666453fd8e57a0ce9e515e4765ae2b60a

/cwetsy/cwetsy/parser/browse_parser.py

a049cb5b8bc4542890ee7856ce7379b97e183bed

[ "MIT" ]

permissive

trujunzhang/djzhang-targets

dc6c3086553a5450fb239cc1cef5330a51a02e1f

c2e327acde9d51f0455e7243f17d93d74b579501

refs/heads/master

2021-01-09T20:52:31.258826

2016-07-16T13:18:53

60,747,429

2

1

null

UTF-8

Python

false

204

py

from cwetsy.parser.base_parser import BaseParser class BrowseParser(BaseParser): def __init__(self): super(BrowseParser, self).__init__() def parse(self, url, hxs): return None

[ "trujunzhang@gmail.com" ]

trujunzhang@gmail.com

68e4256f5b371f2525935ebc77355c859a1a2757

2993adb383fed317e6a83f2b8c2cacd640d19fb3

/bookmarks/account/authentication.py

2a9db5db7359fcc4a5a5ddcca0b1e3170ebbf911

[]

no_license

Dyavathrocky/socialapp

0e811a957a224b30aa32e8a24e3253c1b49a25df

1dc071b69f9258c4f540211e25635ac277a6f6e4

refs/heads/master

2022-12-02T03:42:32.778466

2020-08-21T13:19:25

286,060,425

0

null

UTF-8

Python

false

579

py

from django.contrib.auth.models import User class EmailAuthBackend(object): """ Authenticate using an e-mail address. """ def authenticate(self, request, username=None, password=None): try: user = User.objects.get(email=username) if user.check_password(password): return user return None except User.DoesNotExist: return None def get_user(self, user_id): try: return User.objects.get(pk=user_id) except User.DoesNotExist: return None

[ "davathrak@gmail.com" ]

davathrak@gmail.com

9478688498c1c1a485af4ce8894c0f2948b2b74b

6223dc2e5de7921696cb34fb62142fd4a4efe361

/.metadata/.plugins/org.eclipse.core.resources/.history/25/0083d7fa3b6a00141afa8a8ed49a3dc2

7b564846565a3335ffc0ed085fe8f0d38b42e923

[]

no_license

Mushirahmed/python_workspace

5ef477b2688e8c25b1372f546752501ee53d93e5

46e2ed783b17450aba29e4e2df7b656522b2b03b

refs/heads/master

2021-03-12T19:24:50.598982

2015-05-25T10:23:54

24,671,376

0

1

null

2015-02-06T09:27:40

2014-10-01T08:40:33

Python

UTF-8

Python

false

5,466

#!/usr/bin/env python # # Copyright 2014 <+YOU OR YOUR COMPANY+>. # # This is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 3, or (at your option) # any later version. # # This software is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this software; see the file COPYING. If not, write to # the Free Software Foundation, Inc., 51 Franklin Street, # Boston, MA 02110-1301, USA. # import numpy #from operator import add #import copy #from gnuradio import gr import gras class expo(gras.Block): """ docstring for block expo """ def __init__(self): gras.Block.__init__(self, name="expo", in_sig=[numpy.float32], out_sig=[numpy.float32]) def set_parameters(self,g,a,b): self.gama=g self.alpha=a self.beta=b def yield_times(self): from datetime import date, time, datetime, timedelta start = datetime.combine(date.today(), time(0, 0)) yield start.strftime("%S") while True: start += timedelta(seconds=0.5) yield start.strftime("%S") def work(self, input_items, output_items): in0 = input_items[0] out = output_items[0] tmrg = [] o1 = [] o2 = [] o3 = [] ans = [] final_output = [] gen = self.yield_times() for ii in range(20): tmrg.append(gen.next()) # print "tmrg :",tmrg """for i1 in range(0,10): o1.append((self.gama)/(self.alpha*self.beta)) print "o1 : ", o1 for i2 in range(0,10): o2.append(((self.gama)*(-numpy.exp(self.alpha)))/(self.alpha*(self.beta-self.alpha))) print "o2 : ",o2 for i3 in range(0,10): o3.append(((self.gama)*(-numpy.exp(self.beta)))/(self.beta*(self.alpha-self.beta))) print "o3 : ",o3 #ans.append(o1+o2+o3) for i in range(0,10): ans.append(list(numpy.array(o1[i])+numpy.array(o2[i])+numpy.array(o3[i]))) print "Final Ans : ",ans print "Type out : ",type(out) print "Type ans :",type(ans) out = copy.copy(ans) #out[0:1] = ans print "Output is : " ,out self.consume(0,1) self.produce(0,1)""" #o1.append((self.gama)/(self.alpha*self.beta)) #print "o1 : ", o1 for i in range(0,20): o1.append((self.gama)/(self.alpha*self.beta)) print "o1 : ", o1[i] o2.append(((self.gama)*(numpy.exp(-(self.alpha*in0[0]*i)))/(self.alpha*(self.beta-self.alpha)))) print "o2 : ",o2[i] o3.append(((self.gama)*(numpy.exp(-(self.beta*in0[0]*i)))/(self.beta*(self.alpha-self.beta)))) print "o3 : ",o3[i] ans.append(o1[i]+o2[i]+o3[i]) print "Final Ans : ",ans #print "Type out : ",type(out) #print "Type ans :",type(ans) #out[0:1] = ans #print "Output : ", out[0] """for i in range(0,len(ans)): #out = copy.copy(ans[i]) #out[0:1] = ans #print "Output is : " ,out""" """for i1 in range(0,len(ans)): final_output.append(o1+ans[i1]) print "Final OutPut : ", final_output""" for i1 in range(0,len(ans)): out[0] = ans[i1] print "Output Sent : ", out #out[:len(final_output)] = copy.copy(final_output) self.consume(0,1) self.produce(0,1) """result = [] for i in range(0,20): result.append(numpy.exp(i)) print "Result : ",result out[0] = result self.consume(0,1) self.produce(0,1) """ #o2 = -numpy.exp(-2*in0[0:1]) #o3 = -numpy.exp(-3*in0[0:1]) #o2=numpy.exp(-(in0[0:1]*self.alpha)) #print("o2 :",o2) #o3=numpy.sin((self.freq*in0[0:1])+(self.sigma)) #print("o3 :",o3) #o4=numpy.sqrt(o1-numpy.square(self.zita)) #print("o4 :",o4) """ans = o1-(mul/o4) #ans.append(o1-((numpy.exp(-in0[0:1]*self.sigma)*(numpy.sin((self.freq*in0[0:1])+(self.sigma))))/numpy.sqrt(o1-numpy.square(self.zita)))) print("Final Value : ",ans) out[0:1] = ans""" #o2 = -numpy.exp(-2*tmrg) #o3 = -numpy.exp(-3*in0[0:1]) #o2 = numpy.exp(-in0[0:1]*self.alpha) #o3 = numpy.exp(-in0[0:1]*self.beta) #o4 = numpy.sqrt(1-numpy.square(self.alpha)) #ans = 1-((o2*o3)/o4) #ans.append(o2) #ans.append(o1-((numpy.exp(-in0[0:1]*self.sigma)*(numpy.sin((self.freq*in0[0:1])+(self.sigma))))/numpy.sqrt(o1-numpy.square(self.zita)))) #print("Final Value : ",ans) #out[0:1] = ans #out = copy.copy(ans) #self.consume(0,1) #self.produce(0,1) #return len(output_items[0])

[ "imushir@gmail.com" ]

imushir@gmail.com

d3e241d4b04a38c79e01d0b0348b62f60c6c72fa

b44ba1ca68154a37936ae3822ca016b5d9a99a2a

/Redis/redis_pipe.py

bfde6e48477131440764d56064521f1f1f917c54

[]

no_license

liuxingrichu/advanced-network-program

6e17d30980e21b3397ac5ed5e404a282983a6869

3f84c4600a35af12a68a4c512afbe60ddf6347b1

refs/heads/master

2021-01-23T02:05:45.933255

2017-08-06T09:15:54

85,964,385

0

1

null

UTF-8

Python

false

427

py

#!/usr/bin/env python # -*- coding:utf-8 -*- import redis import time ''' 使用pipeline实现一次请求,执行多条命令 ''' # db的选择范围为0-15 pool = redis.ConnectionPool(host='localhost', port=6379, db=12) r = redis.Redis(connection_pool=pool) # pipe = r.pipeline(transaction=False) pipe = r.pipeline(transaction=True) pipe.set('name', 'Tom') time.sleep(30) pipe.set('role', 'teacher') pipe.execute()

[ "liuxingrichu@163.com" ]

liuxingrichu@163.com

4c3c98dc139b2f8f584f48a9f1db91fb63471c18

5eea120356afc15cc3edb71f8864d6771ad865c6

/futures/var_model/__init__.py

e9af4c55745c0234467df114b12290c6b8f19f73

[ "MIT" ]

permissive

ShubraChowdhury/Investment_Finance

469d5e5a200616eee830be18cb4a86d54319a30b

3da761d755278d3d2de8c201b56d4ff9cb23def4

refs/heads/master

2022-12-12T11:52:33.585329

2021-09-23T18:13:15

153,317,318

2

0

null

2022-12-08T00:45:34

2018-10-16T16:22:56

Jupyter Notebook

UTF-8

Python

false

312

py

""" The __init__.py files are required to make Python treat the directories as containing packages; this is done to prevent directories with a common name, such as string, from unintentionally hiding valid modules that occur later (deeper) on the module search path. @author: ucaiado Created on 09/05/2016 """

[ "noreply@github.com" ]

ShubraChowdhury.noreply@github.com

91f6f93546e8240aff32445f1e68c11ccfe19d83

4d2238210813c1581bf44f64d8a63196f75d2df4

/tem.py

ece18216c221c476bc14897a6b8a415a8a9197d1

[]

no_license

wwtang/code02

b1600d34907404c81fa523cfdaa74db0021b8bb3

9f03dda7b339d8c310c8a735fc4f6d795b153801

refs/heads/master

2020-12-24T14:10:33.738734

2012-12-14T04:24:47

null

0

null

UTF-8

Python

false

214

py

color = raw_input('please select the color: ') if color == "white" or color == "black": print "the color was black or white" elif color > "k" : print "the color start with letter after the 'K' in alphabet"

[ "andytang1994@gmail.com" ]

andytang1994@gmail.com

a4ce7faf8a9617e3a7dcffa89948c091bf32dc3f

1e11d6f9245c55e21edfb24f4340d52e3f7f327f

/dillo/migrations/0078_organizations.py

ecdc1eed4f69e90c13232e53b67ef2f646fc6389

[]

no_license

armadillica/dillo

996e8462f4f76349ecc49ecb08cdd6c8c66e072b

960aed85f8438109bed9883321891305e1db8b10

refs/heads/main

2023-08-04T06:45:34.570071

2023-06-04T00:07:57

30,461,275

79

18

null

2023-08-02T00:22:40

2015-02-07T16:17:43

Python

UTF-8

Python

false

4,925

py

# Generated by Django 3.2.13 on 2022-11-19 22:29 import dillo.models.mixins from django.conf import settings from django.db import migrations, models import django.db.models.deletion import django_countries.fields def forwards_func(apps, schema_editor): """Set default cateogries.""" OrganizationCategory = apps.get_model('dillo', 'OrganizationCategory') db_alias = schema_editor.connection.alias for c in {'3D', '2D', 'Features', 'Shorts', 'Games'}: OrganizationCategory.objects.using(db_alias).create(name=c) class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('dillo', '0077_profile_job'), ] operations = [ migrations.CreateModel( name='OrganizationCategory', fields=[ ( 'id', models.BigAutoField( auto_created=True, primary_key=True, serialize=False, verbose_name='ID' ), ), ('name', models.CharField(max_length=128, unique=True)), ], options={ 'verbose_name_plural': 'Organization categories', }, ), migrations.CreateModel( name='Organization', fields=[ ( 'id', models.BigAutoField( auto_created=True, primary_key=True, serialize=False, verbose_name='ID' ), ), ( 'created_at', models.DateTimeField(auto_now_add=True, verbose_name='date created'), ), ('updated_at', models.DateTimeField(auto_now=True, verbose_name='date edited')), ('name', models.CharField(max_length=255, unique=True)), ( 'visibility', models.CharField( choices=[ ('public', 'Public'), ('unlisted', 'Unlisted'), ('under_review', 'Under Review'), ], default='under_review', max_length=16, ), ), ( 'description', models.TextField( blank=True, help_text='A description of the organization activities.', null=True, ), ), ('website', models.URLField(max_length=120)), ( 'logo', models.ImageField( blank=True, height_field='logo_height', upload_to=dillo.models.mixins.get_upload_to_hashed_path, width_field='logo_width', help_text='A square picture, around 512x512.', ), ), ('logo_height', models.PositiveIntegerField(null=True)), ('logo_width', models.PositiveIntegerField(null=True)), ('city', models.CharField(blank=True, max_length=256, null=True)), ( 'country', django_countries.fields.CountryField(blank=True, max_length=2, null=True), ), ( 'is_online', models.BooleanField( default=False, help_text='Operates fully online, with no physical HQ.' ), ), ('is_active', models.BooleanField(default=True)), ( 'categories', models.ManyToManyField( help_text='Keywords to identify this organization.', null=True, to='dillo.OrganizationCategory', ), ), ( 'city_ref', models.ForeignKey( blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='organizations', to='dillo.city', ), ), ( 'user', models.ForeignKey( null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, ), ), ], options={ 'abstract': False, }, ), migrations.RunPython(forwards_func, migrations.RunPython.noop), ]

[ "francesco.siddi@gmail.com" ]

francesco.siddi@gmail.com

95482e1fc560e2c251c59b36d951f928ba1157ba

06292f96cba132ca57777672a447cfff7c5abee6

/week5/tut/submit/1.py

b099a6a693b68bb37a739181ac6b9f40fa36844d

[]

no_license

kietteik/ppl

1746440b12affe71e67d6f958922b32b1fdaab5c

2ee60582e81595b8d8b5d0f8212d20151cfe9264

refs/heads/master

2023-03-01T00:24:36.969189

2021-01-31T05:15:13

305,802,556

0

null

UTF-8

Python

false

238

py

def double(lst): '''1. a''' return [i * 2 for i in lst] def double(lst): '''1. b''' if not lst: return [] return [lst[0] * 2] + double(lst[1:]) def double(lst): '''1. c''' return list(map(lambda x: x * 2, lst))

[ "kietteikdoi@gmail.com" ]

kietteikdoi@gmail.com

c469f6d0359884d8d16ed851a6af1e7f39b15f42

6f04b7f8fd55fffb54ce4c78049812655b8c176b

/chap03_GroupApply/lecture/step02_groupby_plot_선생님.py

a33aaf98830f6e875d4ec23df91b81e5c56e0c20

[]

no_license

Elly-bang/Python-ll

71092507b719e1532675f8bab489be3f7366c1de

2658de214cc4a9dd68ad35d82202b59b3129e5af

refs/heads/master

2022-11-09T18:11:55.449732

2020-06-30T06:57:11

276,021,248

0

null

UTF-8

Python

false

2,962

py

# -*- coding: utf-8 -*- """ 집단변수 기준 자료 분석 - subset 생성 - group 객체 생성 - 시각화 """ import pandas as pd # 1. dataset load wine = pd.read_csv('C:/ITWILL/4_Python-II/data/winequality-both.csv') wine.info() # type, quality # 칼럼명 변경 : 공백 -> '_' 교체 wine.columns = wine.columns.str.replace(' ', '_') wine.info() # RangeIndex: 6497 entries, 0 to 6496 # Data columns (total 13 columns) # 집단변수 확인 wine['type'].unique() # ['red', 'white'] wine.quality.unique() # [5, 6, 7, 4, 8, 3, 9] # 2. subset 생성 # 1) type 칼럼 : DataFrame(2차원) red_wine = wine.loc[wine['type']=='red'] #[row, col] red_wine.info() # Int64Index: 1599 entries, 0 to 1598 # Data columns (total 13 columns): red_wine.shape # (1599, 13) # 2) type(행) vs quality(열) : Series(1차원) red_quality = wine.loc[wine['type']=='red', 'quality']#[행, 열] type(red_quality) # pandas.core.series.Series red_quality.shape # (1599,) white_quality = wine.loc[wine['type']=='white', 'quality']#[행, 열] type(white_quality) # pandas.core.series.Series white_quality.shape # (4898,) # 3. group 객체 생성 : 집단변수 2개 -> 11변수 그룹화 # 형식) DF.groupby(['칼럼1', '칼럼2']) wine_grp = wine.groupby(['type', 'quality']) # 각 그룹의 빈도수 wine_grp.size() ''' type quality red 3 10 4 53 5 681 6 638 7 199 8 18 white 3 20 4 163 ''' # 1d -> 2d : 교차분할표 grp_2d = wine_grp.size().unstack() grp_2d ''' quality 3 4 5 6 7 8 9 type red 10.0 53.0 681.0 638.0 199.0 18.0 NaN white 20.0 163.0 1457.0 2198.0 880.0 175.0 5.0 ''' # 교차분할표 tab = pd.crosstab(wine['type'], wine['quality']) # (index=행, columns=열) tab ''' quality 3 4 5 6 7 8 9 type red 10 53 681 638 199 18 0 white 20 163 1457 2198 880 175 5 ''' # 4. group 객체 시각화 import matplotlib.pyplot as plt type(grp_2d) # pandas.core.frame.DataFrame # 누적형 가로막대 grp_2d.plot(kind='barh', title='type vs quality', stacked=True) plt.show() # 5. wine 종류(집단변수) vs 알콜(연속형) 통계량 wine_grp = wine.groupby('type') # 집단변수 1개 -> 12개 변수 그룹화 # 각 집단별 알콜 요약통계량 wine_grp['alcohol'].describe() ''' count mean std min 25% 50% 75% max type red 1599.0 10.422983 1.065668 8.4 9.5 10.2 11.1 14.9 white 4898.0 10.514267 1.230621 8.0 9.5 10.4 11.4 14.2 '''

[ "noreply@github.com" ]

Elly-bang.noreply@github.com

03ae5a477c8f067d8cb700f67401521690fd068d

eda9187adfd53c03f55207ad05d09d2d118baa4f

/algo/pca/pca_old.py

264da244de8c2b727e5ca60a969c58a436681e39

[]

no_license

HuiZhaozh/python_tutorials

168761c9d21ad127a604512d7c6c6b38b4faa3c7

bde4245741081656875bcba2e4e4fcb6b711a3d9

refs/heads/master

2023-07-07T20:36:20.137647

2020-04-24T07:18:25

null

0

null

UTF-8

Python

false

2,519

py

# -*- coding:utf-8 -*- # /usr/bin/python ''' @Author: Yan Errol @Email:2681506@gmail.com @Date: 2019-06-09 23:59 @Describe: @Evn: ''' from sklearn.decomposition import PCA import matplotlib.pyplot as plt import numpy as np # A value we picked to always display the same results # Feel free to change this to any value greater than 0 view different random value outcomes seed = 9000 # We're using a seeded random state so we always get the same outcome seeded_state = np.random.RandomState(seed=seed) # Returns a random 150 points (x, y pairs) in a gaussian distribution, # IE most of the points fall close to the average with a few outliers rand_points = seeded_state.randn(150, 2) # The @ operator performs matrix multiplication, and serves to bring # our gaussian distribution points closer together points = rand_points @ seeded_state.rand(2, 2) x = points[:, 0] y = points[:, 1] # Now we have a sample dataset of 150 points to perform PCA on, so # go ahead and display this in a plot. plt.scatter(x, y, alpha=0.5) plt.title("Sample Dataset") print("Plotting our created dataset...\n") print("Points:") for p in points[:10, :]: print("({:7.4f}, {:7.4f})".format(p[0], p[1])) print("...\n") plt.show() # Find two principal components from our given dataset pca = PCA(n_components = 2) pca.fit(points) # Once we are fitted, we have access to inner mean_, components_, and explained_variance_ variables # Use these to add some arrows to our plot plt.scatter(x, y, alpha=0.5) plt.title("Sample Dataset with Principal Component Lines") for var, component in zip(pca.explained_variance_, pca.components_): plt.annotate( "", component * np.sqrt(var) * 2 + pca.mean_, pca.mean_ ) print("Plotting our calculated principal components...\n") plt.show() # Reduce the dimensionality of our data using a PCA transformation pca = PCA(n_components = 1) transformed_points = pca.fit_transform(points) # Note that all the inverse transformation does is transforms the data to its original space. # In practice, this is unnecessary. For this example, all data would be along the x axis. # We use it here for visualization purposes inverse = pca.inverse_transform(transformed_points) t_x = inverse[:, 0] t_y = inverse[:, 0] # Plot the original and transformed data sets plt.scatter(x, y, alpha=0.3) plt.scatter(t_x, t_y, alpha=0.7) plt.title("Sample Dataset (Blue) and Transformed Dataset (Orange)") print("Plotting our dataset with a dimensionality reduction...") plt.show()

[ "2681506@gmail.com" ]

2681506@gmail.com

c3029c19a6c3b697bb29649019096a2ef9384915

521efcd158f4c69a686ed1c63dd8e4b0b68cc011

/airflow/operators/datetime.py

47021c1730952719ea17c0bf05c4778c8d57ae5f

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

permissive

coutureai/RaWorkflowOrchestrator

33fd8e253bfea2f9a82bb122ca79e8cf9dffb003

cd3ea2579dff7bbab0d6235fcdeba2bb9edfc01f

refs/heads/main

2022-10-01T06:24:18.560652

2021-12-29T04:52:56

184,547,783

5

12

Apache-2.0

2022-11-04T00:02:55

2019-05-02T08:38:38

Python

UTF-8

Python

false

4,632

py

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import datetime from typing import Iterable, Union from airflow.exceptions import AirflowException from airflow.operators.branch import BaseBranchOperator from airflow.utils import timezone from airflow.utils.context import Context class BranchDateTimeOperator(BaseBranchOperator): """ Branches into one of two lists of tasks depending on the current datetime. For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BranchDateTimeOperator` True branch will be returned when ``datetime.datetime.now()`` falls below ``target_upper`` and above ``target_lower``. :param follow_task_ids_if_true: task id or task ids to follow if ``datetime.datetime.now()`` falls above target_lower and below ``target_upper``. :type follow_task_ids_if_true: str or list[str] :param follow_task_ids_if_false: task id or task ids to follow if ``datetime.datetime.now()`` falls below target_lower or above ``target_upper``. :type follow_task_ids_if_false: str or list[str] :param target_lower: target lower bound. :type target_lower: Optional[datetime.datetime] :param target_upper: target upper bound. :type target_upper: Optional[datetime.datetime] :param use_task_execution_date: If ``True``, uses task's execution day to compare with targets. Execution date is useful for backfilling. If ``False``, uses system's date. :type use_task_execution_date: bool """ def __init__( self, *, follow_task_ids_if_true: Union[str, Iterable[str]], follow_task_ids_if_false: Union[str, Iterable[str]], target_lower: Union[datetime.datetime, datetime.time, None], target_upper: Union[datetime.datetime, datetime.time, None], use_task_execution_date: bool = False, **kwargs, ) -> None: super().__init__(**kwargs) if target_lower is None and target_upper is None: raise AirflowException( "Both target_upper and target_lower are None. At least one " "must be defined to be compared to the current datetime" ) self.target_lower = target_lower self.target_upper = target_upper self.follow_task_ids_if_true = follow_task_ids_if_true self.follow_task_ids_if_false = follow_task_ids_if_false self.use_task_execution_date = use_task_execution_date def choose_branch(self, context: Context) -> Union[str, Iterable[str]]: if self.use_task_execution_date is True: now = timezone.make_naive(context["logical_date"], self.dag.timezone) else: now = timezone.make_naive(timezone.utcnow(), self.dag.timezone) lower, upper = target_times_as_dates(now, self.target_lower, self.target_upper) if upper is not None and upper < now: return self.follow_task_ids_if_false if lower is not None and lower > now: return self.follow_task_ids_if_false return self.follow_task_ids_if_true def target_times_as_dates( base_date: datetime.datetime, lower: Union[datetime.datetime, datetime.time, None], upper: Union[datetime.datetime, datetime.time, None], ): """Ensures upper and lower time targets are datetimes by combining them with base_date""" if isinstance(lower, datetime.datetime) and isinstance(upper, datetime.datetime): return lower, upper if lower is not None and isinstance(lower, datetime.time): lower = datetime.datetime.combine(base_date, lower) if upper is not None and isinstance(upper, datetime.time): upper = datetime.datetime.combine(base_date, upper) if lower is None or upper is None: return lower, upper if upper < lower: upper += datetime.timedelta(days=1) return lower, upper

[ "noreply@github.com" ]

coutureai.noreply@github.com

734b6a332d6f0af9cd41c64282aff3d00bb8662f

461bffdd97ba507b29f1fbf6f9af1800f0e241f6

/pytext/metric_reporters/classification_metric_reporter.py

1e3ced78d285a9bff886349e7b06f32ac39129b1

[ "BSD-3-Clause" ]

permissive

Erica-Liu/pytext

d347e1327254bbe746c491fd8002bcc2e29d82a9

0a77e34e555750311ede54514c3c85b133b258f3

refs/heads/master

2020-06-16T02:49:21.589774

2019-07-05T18:25:52

2019-07-05T18:33:55

195,459,270

0

NOASSERTION

2019-07-05T19:38:34

null

UTF-8

Python

false

6,254

py

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved from enum import Enum from typing import List, Optional from pytext.common.constants import Stage from pytext.data import CommonMetadata from pytext.metrics import ( LabelListPrediction, LabelPrediction, compute_classification_metrics, compute_multi_label_classification_metrics, ) from .channel import Channel, ConsoleChannel, FileChannel from .metric_reporter import MetricReporter META_LABEL_NAMES = "label_names" class IntentModelChannel(FileChannel): def get_title(self): return ("predicted", "actual", "scores_str", "text") def gen_content(self, metrics, loss, preds, targets, scores, contexts): for i in range(len(preds)): yield [ preds[i], targets[i], ",".join([f"{s:.2f}" for s in scores[i]]), contexts["utterance"][i], ] class ComparableClassificationMetric(Enum): ACCURACY = "accuracy" ROC_AUC = "roc_auc" MCC = "mcc" MACRO_F1 = "macro_f1" LABEL_F1 = "label_f1" LABEL_AVG_PRECISION = "label_avg_precision" LABEL_ROC_AUC = "label_roc_auc" # use negative because the reporter's lower_is_better value is False NEGATIVE_LOSS = "negative_loss" class ClassificationMetricReporter(MetricReporter): __EXPANSIBLE__ = True class Config(MetricReporter.Config): model_select_metric: ComparableClassificationMetric = ( ComparableClassificationMetric.ACCURACY ) target_label: Optional[str] = None #: These column names correspond to raw input data columns. Text in these #: columns (usually just 1 column) will be concatenated and output in #: the IntentModelChannel as an evaluation tsv. text_column_names: List[str] = ["text"] def __init__( self, label_names: List[str], channels: List[Channel], model_select_metric: ComparableClassificationMetric = ( ComparableClassificationMetric.ACCURACY ), target_label: Optional[str] = None, text_column_names: List[str] = Config.text_column_names, ) -> None: super().__init__(channels) self.label_names = label_names self.model_select_metric = model_select_metric self.target_label = target_label self.text_column_names = text_column_names @classmethod def from_config(cls, config, meta: CommonMetadata = None, tensorizers=None): # TODO: refactor metric reporting and remove this hack if tensorizers: labels = list(tensorizers["labels"].vocab) else: labels = meta.target.vocab.itos return cls.from_config_and_label_names(config, labels) @classmethod def from_config_and_label_names(cls, config, label_names: List[str]): if config.model_select_metric in ( ComparableClassificationMetric.LABEL_F1, ComparableClassificationMetric.LABEL_AVG_PRECISION, ComparableClassificationMetric.LABEL_ROC_AUC, ): assert config.target_label is not None assert config.target_label in label_names if config.model_select_metric in ( ComparableClassificationMetric.ROC_AUC, ComparableClassificationMetric.MCC, ): assert len(label_names) == 2 return cls( label_names, [ConsoleChannel(), IntentModelChannel((Stage.TEST,), config.output_path)], config.model_select_metric, config.target_label, config.text_column_names, ) def batch_context(self, raw_batch, batch): context = super().batch_context(raw_batch, batch) context["utterance"] = [ " | ".join(str(row[column_name]) for column_name in self.text_column_names) for row in raw_batch ] return context def calculate_metric(self): return compute_classification_metrics( [ LabelPrediction(scores, pred, expect) for scores, pred, expect in zip( self.all_scores, self.all_preds, self.all_targets ) ], self.label_names, self.calculate_loss(), ) def get_meta(self): return {META_LABEL_NAMES: self.label_names} def get_model_select_metric(self, metrics): if self.model_select_metric == ComparableClassificationMetric.ACCURACY: metric = metrics.accuracy elif self.model_select_metric == ComparableClassificationMetric.ROC_AUC: metric = metrics.roc_auc elif self.model_select_metric == ComparableClassificationMetric.MCC: metric = metrics.mcc elif self.model_select_metric == ComparableClassificationMetric.MACRO_F1: metric = metrics.macro_prf1_metrics.macro_scores.f1 elif self.model_select_metric == ComparableClassificationMetric.LABEL_F1: metric = metrics.macro_prf1_metrics.per_label_scores[self.target_label].f1 elif ( self.model_select_metric == ComparableClassificationMetric.LABEL_AVG_PRECISION ): metric = metrics.per_label_soft_scores[self.target_label].average_precision elif self.model_select_metric == ComparableClassificationMetric.LABEL_ROC_AUC: metric = metrics.per_label_soft_scores[self.target_label].roc_auc elif self.model_select_metric == ComparableClassificationMetric.NEGATIVE_LOSS: metric = -metrics.loss else: raise ValueError(f"unknown metric: {self.model_select_metric}") assert metric is not None return metric class MultiLabelClassificationMetricReporter(ClassificationMetricReporter): def calculate_metric(self): return compute_multi_label_classification_metrics( [ LabelListPrediction(scores, pred, expect) for scores, pred, expect in zip( self.all_scores, self.all_preds, self.all_targets ) ], self.label_names, self.calculate_loss(), )

[ "facebook-github-bot@users.noreply.github.com" ]

facebook-github-bot@users.noreply.github.com

8f6c010d69c13e262cdd609efe3ac4b6009f38d3

6dae31f10260e39feae9d268e3ebe6d23146575a

/spm/bin_deep_surveys/run_stellarpop_miles_deep2_kroupa

fc11bb5287636c2c426dae12945d749d5984c5b1

[ "CC0-1.0" ]

permissive

JohanComparat/pySU

e55eba92f0660e733468bce618595a03dc25a3d2

4169e11414be661dc0c01c774e64fb8ce6242825

refs/heads/master

2021-12-25T11:06:04.315554

2021-10-11T12:03:22

44,340,565

1

2

null

UTF-8

Python

false

2,277

#! /usr/bin/env python import sys from os.path import join import os import time import numpy as np import glob import astropy.cosmology as co cosmo = co.Planck13 import astropy.io.fits as fits # for one galaxy spectrum import GalaxySpectrumFIREFLY as gs import StellarPopulationModel as spm catalog=fits.open(join(os.environ['DEEP2_DIR'], "catalogs", "zcat.deep2.dr4.v4.LFcatalogTC.Planck15.fits"))[1].data outputFolder = join( os.environ['DEEP2_DIR'], 'stellarpop-m11-kroupa-miles', 'stellarpop') def runSpec(catalog_entry): print catalog_entry['ZBEST'], catalog_entry['RA'], catalog_entry['DEC'] t0=time.time() mask=str(catalog_entry['MASK']) objno=str(catalog_entry['OBJNO']) path_to_spectrum = glob.glob(join(os.environ['DEEP2_DIR'], 'spectra', mask, '*', '*' + objno + '*_fc_tc.dat')) if len(path_to_spectrum)>=1: try: spec=gs.GalaxySpectrumFIREFLY("-", milky_way_reddening=True) spec.openObservedDEEP2pectrum(catalog_entry) ageMax = np.log10(cosmo.age(spec.redshift).value*1e9) if spec.redshift>0.01 and spec.redshift < 1.7 : model = spm.StellarPopulationModel(spec, join(outputFolder , 'spFly-deep2-'+mask+'-'+objno ), cosmo, models = 'm11', model_libs = ['MILES'], imfs = ['kr'], age_limits = [6,10], downgrade_models = True, data_wave_medium = 'air', Z_limits = [-3.,1.],suffix="-kr.fits", use_downgraded_models = True) try : model.fit_models_to_data() #print( model.averages ) except (ValueError): pass print "time used =", time.time()-t0 ,"seconds" except (IndexError): pass for catalog_entry in catalog[::-1]: mask=str(catalog_entry['MASK']) objno=str(catalog_entry['OBJNO']) if os.path.isfile(join(outputFolder , 'spFly-deep2-'+mask+'-'+objno +"-kr.fits")): print "pass", join(outputFolder , 'spFly-deep2-'+mask+'-'+objno +"-kr.fits") else: runSpec(catalog_entry) sys.exit() n_fc_tc = n.zeros_like(catalog['ZBEST']) for ii, catalog_entry in enumerate(catalog): mask=str(catalog_entry['MASK']) objno=str(catalog_entry['OBJNO']) path_to_spectrum = glob.glob(join(os.environ['DEEP2_DIR'], 'spectra', mask, '*', '*' + objno + '*_fc_tc.dat')) n_fc_tc[ii] = len(path_to_spectrum ) ok=(catalog['ZBEST']>0.01)&(catalog['ZBEST']<1.7)&(n_fc_tc>=1) print len(catalog), len(catalog[ok])

[ "johan.comparat@gmail.com" ]

johan.comparat@gmail.com

ff6f46df45a62d02b5d3eb10ff5fa6488d3aca62

ea01ed735850bf61101b869b1df618d3c09c2aa3

/python基础/network_programming/ftp_task/ftp/conf/settings.py

fe1097cb50a4b2bf3c4804ce40907ffed75bb71a

[]

no_license

liuzhipeng17/python-common

867c49ac08719fabda371765d1f9e42f6dd289b9

fb44da203d4e3a8304d9fe6205e60c71d3a620d8

refs/heads/master

2021-09-27T10:39:45.178135

2018-11-08T01:49:33

null

0

null

UTF-8

Python

false

1,296

py

# -*- coding: utf-8 -*- import os.path _project_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) USER_DB_PATH = os.path.join(_project_path, 'db', 'userdb.ini') ENCODING = 'utf-8' MAX_BUFFER_SIZE = 1024 USER_BASE_PATH = os.path.join(_project_path, 'dir', 'home') BASE_DIR = os.path.join(_project_path, 'dir') USER_DOWNLOAD_BASE_DIR = os.path.join(_project_path, 'dir', 'downloads') USER_UPLOAD_BASE_DIR = os.path.join(_project_path, 'dir', 'uploads') STATUS_CODE = { 200 : "Task finished", 250 : "Invalid cmd format, e.g: {'action':'get','filename':'tests.py','size':344}", 251 : "Invalid cmd ", 252 : "Invalid auth data", 253 : "Wrong username or password", 254 : "Passed authentication", 255 : "Filename doesn't provided", 256 : "File doesn't exist on server", 257 : "ready to send file", 258 : "md5 verification", 259 : "path doesn't exist on server", 260 : "path changed", 261 : "send File line", 262 : "File has exist on server", 263 : "Put empty file", 264 : "Put not null file", 265 : "Get empty file", 266 : "Path access permitted or Path not exist", 267 : "pwd invalid cmd arguments", 268 : "pwd pass", 269 : "permitted putting same-name file unless continue situation" }

[ "liucpliu@sina.cn" ]

liucpliu@sina.cn

e1550eadd9cc69970c6b6044d39bd284e1baef25

474525154a4e1d48ef5242d1f44164d05399b145

/spinoffs/oryx/oryx/experimental/nn/function.py

b9d20e453f86199f85885faeeef667bb5300a2ac

[ "Apache-2.0" ]

permissive

svshivapuja/probability

9855737790f74a39169688fbfec9671deef804d9

af7ccb22d972329633530c3b754ed1f49472f6a7

refs/heads/main

2023-07-17T04:14:53.703622

2021-08-30T17:47:06

400,983,015

1

0

Apache-2.0

2021-08-29T07:51:29

null

UTF-8

Python

false

1,863

py

# Copyright 2020 The TensorFlow Probability 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. # ============================================================================ # Lint as: python3 """Registers custom rules for neural networks in the stateful function API. The Oryx state API enables having a custom unzip rules when `init`-ing a function. We use this for neural networks to thread kwargs through the Jaxpr that is created when unzipping a function. This module implements this by first replacing instances of `layer_cau` with a `FlatPrimitive`s, which avoids using a call primitive, which we would be difficult to pass new keyword arguments into. We can more easily override the behavior of a regular primitive. """ from jax import tree_util from oryx.core import state from oryx.experimental.nn import base __all__ = [ ] def layer_cau_kwargs_rule(*flat_args, num_consts, in_tree, kwargs, **_): """Custom kwargs rule for layer_cau primitive.""" flat_args = flat_args[num_consts:] layer, *args = tree_util.tree_unflatten(in_tree, flat_args) kwargs = dict(kwargs) has_rng = kwargs.pop('has_rng', False) if has_rng: rng, args = args[0], args[1:] kwargs = dict(kwargs, rng=rng) ans = layer.call_and_update(*args, **kwargs) return tree_util.tree_leaves(ans) state.kwargs_rules[base.layer_cau_p] = layer_cau_kwargs_rule

[ "gardener@tensorflow.org" ]

gardener@tensorflow.org

b55ecc78784e9edeb59f797fac7f6750b1ccd7e5

79c0358277a5f6ae231d89ee4476cb1facd00e50

/extra/desktop/gnome/addons/gnome-color-manager/actions.py

c37eddcb3525032b734864d2c7b456d5bc8496bb

[]

no_license

mrust1/PisiLinux

a139dbc9f8d3d61ebec38d08f36dfa6eafff7107

a2014b6912df50ad22da5b2f3d21bf01cbd8e192

refs/heads/master

2020-12-11T03:42:50.309869

2014-10-05T14:05:17

24,826,519

1

0

null

UTF-8

Python

false

663

py

#!/usr/bin/python # -*- coding: utf-8 -*- # # Licensed under the GNU General Public License, version 3. # See the file http://www.gnu.org/licenses/gpl.txt from pisi.actionsapi import autotools from pisi.actionsapi import pisitools from pisi.actionsapi import shelltools from pisi.actionsapi import get def setup(): autotools.configure("--libexecdir=/usr/lib/gnome-color-manager") def build(): autotools.make() def install(): autotools.rawInstall("DESTDIR=%s" % get.installDIR()) pisitools.insinto("/usr/share/pixmaps", "data/icons/48x48/gnome-color-manager.png") pisitools.dodoc("AUTHORS", "COPYING", "ChangeLog", "NEWS", "README")

[ "namso-01@hotmail.it" ]

namso-01@hotmail.it

656b9a478e48b1c9114cb46915cfa1113d2c3a9e

651a296c8f45b5799781fd78a6b5329effe702a0

/polpak/bell_values.py

22a15e0802b2391a06bf53d6f330732079415995

[]

no_license

pdhhiep/Computation_using_Python

095d14370fe1a01a192d7e44fcc81a52655f652b

407ed29fddc267950e9860b8bbd1e038f0387c97

refs/heads/master

2021-05-29T12:35:12.630232

2015-06-27T01:05:17

null

0

null

UTF-8

Python

false

3,625

py

#!/usr/bin/env python # def bell_values ( n_data ): #*****************************************************************************80 # ## BELL_VALUES returns some values of the Bell numbers. # # Discussion: # # The Bell number B(N) is the number of restricted growth functions on N. # # Note that the Stirling numbers of the second kind, S^m_n, count the # number of partitions of N objects into M classes, and so it is # true that # # B(N) = S^1_N + S^2_N + ... + S^N_N. # # The Bell numbers were named for Eric Temple Bell. # # In Mathematica, the function can be evaluated by # # Sum[StirlingS2[n,m],{m,1,n}] # # The Bell number B(N) is defined as the number of partitions (of # any size) of a set of N distinguishable objects. # # A partition of a set is a division of the objects of the set into # subsets. # # Example: # # There are 15 partitions of a set of 4 objects: # # (1234), # (123) (4), # (124) (3), # (12) (34), # (12) (3) (4), # (134) (2), # (13) (24), # (13) (2) (4), # (14) (23), # (1) (234), # (1) (23) (4), # (14) (2) (3), # (1) (24) (3), # (1) (2) (34), # (1) (2) (3) (4). # # and so B(4) = 15. # # First values: # # N B(N) # 0 1 # 1 1 # 2 2 # 3 5 # 4 15 # 5 52 # 6 203 # 7 877 # 8 4140 # 9 21147 # 10 115975 # # Recursion: # # B(I) = sum ( 1 <= J <=I ) Binomial ( I-1, J-1 ) * B(I-J) # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 23 November 2014 # # Author: # # John Burkardt # # Reference: # # Milton Abramowitz and Irene Stegun, # Handbook of Mathematical Functions, # US Department of Commerce, 1964. # # Stephen Wolfram, # The Mathematica Book, # Fourth Edition, # Wolfram Media / Cambridge University Press, 1999. # # Parameters: # # Input/output, integer N_DATA. The user sets N_DATA to 0 before the # first call. On each call, the routine increments N_DATA by 1, and # returns the corresponding data; when there is no more data, the # output value of N_DATA will be 0 again. # # Output, integer N, the order of the Bell number. # # Output, integer C, the value of the Bell number. # import numpy as np n_max = 11 c_vec = np.array ( ( 1, 1, 2, 5, 15, 52, 203, 877, 4140, 21147, 115975 ) ) n_vec = np.array ( ( 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ) ) if ( n_data < 0 ): n_data = 0 if ( n_max <= n_data ): n_data = 0 n = 0 c = 0 else: n = n_vec[n_data] c = c_vec[n_data] n_data = n_data + 1 return n_data, n, c def bell_values_test ( ): #*****************************************************************************80 # ## BELL_VALUES_TEST demonstrates the use of BELL_VALUES. # # Licensing: # # This code is distributed under the GNU LGPL license. # # Modified: # # 23 November 2014 # # Author: # # John Burkardt # print '' print 'BELL_VALUES_TEST:' print ' BELL_VALUES returns values of' print ' the Bell numbers.' print '' print ' N BELL(N)' print '' n_data = 0 while ( True ): n_data, n, c = bell_values ( n_data ) if ( n_data == 0 ): break print '%6d %10d' % ( n, c ) print '' print 'BELL_VALUES_TEST:' print ' Normal end of execution.' return if ( __name__ == '__main__' ): from timestamp import timestamp timestamp ( ) bell_values_test ( ) timestamp ( )

[ "siplukabir@gmail.com" ]

siplukabir@gmail.com

e636e89dc9a0a67ae30601cbdb6cdcf9947fef12

e4f2aba6cb66ac33c5fc439374e8ef39d0bb0e4a

/Week-2-format-string/Exercise-4.py

7d00cc9ba3f0f3a488faa705797ac2907d073325

[]

no_license

AChen24562/Python-QCC

573f5b545239aa24b8047c74539ca6b3e997faa0

1da01b76e209eb9b0d08f0f205d635bc2a149dfd

refs/heads/master

2023-02-06T23:18:41.850377

2020-12-28T12:59:29

289,614,327

0

null

UTF-8

Python

false

213

py

width = 17 height = 12.0 delimiter = "." print(width//2, type(width//2)) print(width/2.0, type(width/2.0)) print(height/3, type(height/3)) # delimiter * 5 = '.....', str print(delimiter * 5, type(delimiter * 5))

[ "54772925+AChen24562@users.noreply.github.com" ]

54772925+AChen24562@users.noreply.github.com

307a62915d6949a0d0da070e0c930329d1b02074

82b946da326148a3c1c1f687f96c0da165bb2c15

/sdk/python/pulumi_azure_native/compute/v20180601/get_log_analytic_export_request_rate_by_interval.py

3eff60bb02dd42eaf3cbb6765a0555d41fb0c38f

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

permissive

morrell/pulumi-azure-native

3916e978382366607f3df0a669f24cb16293ff5e

cd3ba4b9cb08c5e1df7674c1c71695b80e443f08

refs/heads/master

2023-06-20T19:37:05.414924

2021-07-19T20:57:53

387,815,163

0

Apache-2.0

2021-07-20T14:18:29

2021-07-20T14:18:28

null

UTF-8

Python

false

3,956

py

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities from . import outputs from ._enums import * __all__ = [ 'GetLogAnalyticExportRequestRateByIntervalResult', 'AwaitableGetLogAnalyticExportRequestRateByIntervalResult', 'get_log_analytic_export_request_rate_by_interval', ] @pulumi.output_type class GetLogAnalyticExportRequestRateByIntervalResult: """ LogAnalytics operation status response """ def __init__(__self__, properties=None): if properties and not isinstance(properties, dict): raise TypeError("Expected argument 'properties' to be a dict") pulumi.set(__self__, "properties", properties) @property @pulumi.getter def properties(self) -> 'outputs.LogAnalyticsOutputResponse': """ LogAnalyticsOutput """ return pulumi.get(self, "properties") class AwaitableGetLogAnalyticExportRequestRateByIntervalResult(GetLogAnalyticExportRequestRateByIntervalResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetLogAnalyticExportRequestRateByIntervalResult( properties=self.properties) def get_log_analytic_export_request_rate_by_interval(blob_container_sas_uri: Optional[str] = None, from_time: Optional[str] = None, group_by_operation_name: Optional[bool] = None, group_by_resource_name: Optional[bool] = None, group_by_throttle_policy: Optional[bool] = None, interval_length: Optional['IntervalInMins'] = None, location: Optional[str] = None, to_time: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetLogAnalyticExportRequestRateByIntervalResult: """ LogAnalytics operation status response :param str blob_container_sas_uri: SAS Uri of the logging blob container to which LogAnalytics Api writes output logs to. :param str from_time: From time of the query :param bool group_by_operation_name: Group query result by Operation Name. :param bool group_by_resource_name: Group query result by Resource Name. :param bool group_by_throttle_policy: Group query result by Throttle Policy applied. :param 'IntervalInMins' interval_length: Interval value in minutes used to create LogAnalytics call rate logs. :param str location: The location upon which virtual-machine-sizes is queried. :param str to_time: To time of the query """ __args__ = dict() __args__['blobContainerSasUri'] = blob_container_sas_uri __args__['fromTime'] = from_time __args__['groupByOperationName'] = group_by_operation_name __args__['groupByResourceName'] = group_by_resource_name __args__['groupByThrottlePolicy'] = group_by_throttle_policy __args__['intervalLength'] = interval_length __args__['location'] = location __args__['toTime'] = to_time if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:compute/v20180601:getLogAnalyticExportRequestRateByInterval', __args__, opts=opts, typ=GetLogAnalyticExportRequestRateByIntervalResult).value return AwaitableGetLogAnalyticExportRequestRateByIntervalResult( properties=__ret__.properties)

[ "noreply@github.com" ]

morrell.noreply@github.com

ae3b13b10359ae08b10f0782054445f49475fc90

52b5773617a1b972a905de4d692540d26ff74926

/.history/maxProduct_20200731212441.py

c7bb8018626c41179870e4caa9d8418f760ec486

[]

no_license

MaryanneNjeri/pythonModules

56f54bf098ae58ea069bf33f11ae94fa8eedcabc

f4e56b1e4dda2349267af634a46f6b9df6686020

refs/heads/master

2022-12-16T02:59:19.896129

2020-09-11T12:05:22

null

0

null

UTF-8

Python

false

766

py

import sys # time complexity is o(n3 ) and space is o(1) def maxThree(arr): if len(arr) < 3: return -1 maxProduct = -(sys.maxsize -1) print(maxProduct) n = len(arr) for i in range(0,n-2): for j in range(i+1,n-1): for k in range(j+1,n): print('i',arr[i],'j',arr[j],'k',arr[k]) product = arr[i] * arr[j] * arr[k] if product > maxProduct: maxProduct = product return maxProduct # Optimal solution o(nlogn) def maxOp(arr): n = len(arr) arr.sort() first = arr[n-1] * arr[n-2] * arr[n-3] second = arr[0] * arr[1] * arr[n-1] return max(first,second) print(maxOp([-5,-5,4,5])) # O(n) time complexity

[ "mary.jereh@gmail.com" ]

mary.jereh@gmail.com

1699d7d134745de10adce3f9435f31332bfe41fd

635cb7fb75048f9de7b95b48d1f59de68f9b3368

/R09/używanie_metaklas_do_kontrolowania_tworzenia_obiektów/example1.py

e76bc265bf850d4e8c8757ec5aaa9bafea6fbc7d

[]

no_license

anpadoma/python_receptury3

9e889ac503e48eb62160050eecfdc4a64072c184

c761f2c36707785a8a70bdaccebd7533c76dee21

refs/heads/master

2021-01-22T14:38:34.718999

2014-01-31T22:09:44

null

0

null

UTF-8

Python

false

423

py

# example1.py # # Bezpośrednie tworzenie obiektów jest niedozwolone class NoInstances(type): def __call__(self, *args, **kwargs): raise TypeError("Nie można bezpośrednio tworzyć obiektu") class Spam(metaclass=NoInstances): @staticmethod def grok(x): print('Spam.grok') if __name__ == '__main__': try: s = Spam() except TypeError as e: print(e) Spam.grok(42)

[ "mtar@data.pl" ]

mtar@data.pl

c6634f95a8581d8241a4d53c143fe96dbad59ea9

8516f0f456b91c0da6c016b64d68ff2c2cdaf68d

/src/array/intersect.py

1dff47db905e488c248ad540666fbb1ba5276a6f

[]

no_license

huowolf/leetcode

b5bb67206fab6417055b0534c7627bc281a29eef

f34909f09c22d2164bbe21fc7da0361fcbd63fd6

refs/heads/master

2020-03-26T20:20:13.386017

2018-11-20T13:04:03

145,317,787

0

null

UTF-8

Python

false

1,160

py

#https://leetcode-cn.com/explore/interview/card/top-interview-questions-easy/1/array/26/ #两个数组的交集 II #给定两个数组，编写一个函数来计算它们的交集 #=============================================================================== # 输入: nums1 = [1,2,2,1], nums2 = [2,2] # 输出: [2,2] #=============================================================================== class Solution: def intersect(self, nums1, nums2): """ :type nums1: List[int] :type nums2: List[int] :rtype: List[int] """ result=[] #遍历其中一个数组，发现相同元素时添加到新列表中，同时删去另一个数组中的一个相同元素 for i in nums1: for j in nums2: #删除相同元素后，同时跳出该趟搜索 if i==j: result.append(i) nums2.remove(j) break return result nums1 = [1,2,2,1] nums2 = [2,2] l=Solution().intersect(nums1, nums2) print(l) nums1 = [4,9,5] nums2 = [9,4,9,8,4] l=Solution().intersect(nums1, nums2) print(l)

[ "274956285@qq.com" ]

274956285@qq.com

0968ca412075e81decf4567daec9d3887be7f97a

0a2356bde96ebc9b6a82bd91a833bbe04ffb3b82

/myInstagram/migrations/0006_auto_20201019_1230.py

304e84e3452ec7887377156161bd1620a31e667a

[ "MIT" ]

permissive

dancan-sandys/Instagram-clone

3c1ec335f0806ab714e8946fba94e87b17329c78

08cfe2a40f6e701beb6b5fc97a090b61d5e242f3

refs/heads/master

2023-01-01T09:20:52.186988

2020-10-20T11:19:39

304,602,156

0

1

null

UTF-8

Python

false

636

py

# -*- coding: utf-8 -*- # Generated by Django 1.11.29 on 2020-10-19 09:30 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('myInstagram', '0005_remove_photo_profile'), ] operations = [ migrations.AlterField( model_name='photo', name='photo_url', field=models.ImageField(upload_to='photos/'), ), migrations.AlterField( model_name='profile', name='profile_photo', field=models.ImageField(upload_to='profile/'), ), ]

[ "dancan.oruko96@gmail.com" ]

dancan.oruko96@gmail.com

de6ce81cbeb176a956e3e8f4d930d20d3ee38341

1b9bd441c500e79042c48570035071dc20bfaf44

/sources/Yalkut Shimoni/set_alt_structs_nach.py

d8f9d28ee8faf0f6b3ed0e326dc0f06ecfc49d49

[]

no_license

Sefaria/Sefaria-Data

ad2d1d38442fd68943535ebf79e2603be1d15b2b

25bf5a05bf52a344aae18075fba7d1d50eb0713a

refs/heads/master

2023-09-05T00:08:17.502329

2023-08-29T08:53:40

5,502,765

51

52

null

2023-08-29T11:42:31

2012-08-22T00:18:38

null

UTF-8

Python

false

4,419

py

# -*- coding: utf-8 -*- import urllib import urllib2 from urllib2 import URLError, HTTPError import json import pdb import os import sys from bs4 import BeautifulSoup import re p = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) sys.path.insert(0, p) os.environ['DJANGO_SETTINGS_MODULE'] = "sefaria.settings" from local_settings import * sys.path.insert(0, SEFARIA_PROJECT_PATH) from sefaria.model import * def post_index(index): url = SEFARIA_SERVER + '/api/v2/raw/index/Yalkut_Shimoni_on_Nach' indexJSON = json.dumps(index) values = { 'json': indexJSON, 'apikey': API_KEY } data = urllib.urlencode(values) req = urllib2.Request(url, data) try: response = urllib2.urlopen(req) print response.read() except HTTPError, e: print 'Error code: ', e.code def convertIntoRef(line): arr = line.split(",") perek = arr[0] remez = arr[1] para = arr[2] return (perek, Ref("Yalkut Shimoni on Torah."+remez+"."+para)) perakim = {} perakim = { "nodes" : [] } parshiot = { "nodes": [] } title_eng = ["Joshua", "Judges", "I Samuel", "II Samuel", "I Kings", "II Kings", "Isaiah", "Jeremiah", "Ezekiel", "Hosea", "Joel", "Amos", "Obadiah", "Jonah", "Micah", "Nahum", "Habakkuk", "Zephaniah", "Haggai", "Zechariah", "Malachi", "Psalms", "Proverbs", "Job", "Song of Songs", "Ruth", "Lamentations", "Eccelesiastes", "Esther", "Daniel", "Ezra", "Nehemiah", "I Chronicles", "II Chronicles"] title_heb = [u"יהושע", u"שופתים", u"שמואל א", u"שמואל ב", u"מלכים א", u"מלכים ב", u"ישעיהו", u"ירמיהו", u"יחזקאל", u"הושע", u"יואל", u"עמוס", u"עובדיה", u"יונה", u"מיכה", u"נחום", u"חבקוק", u"צפניה", u"חגי", u"זכריה", u"מלאכי", u"תהילים", u"משלי", u"איוב", u"שיר השירים", u"רות", u"איכה", u"קהלת", u"אסתר", u"דניאל", u"עזרא", u"נחמיה", u"דברי הימים א", u"דברי הימים ב"] def getHebrewParsha(parsha): for count, eng in enumerate(title_eng): if eng==parsha: return title_heb[count] for count, title in enumerate(title_eng): f=open("parsha_"+title+".txt", 'r') while True: line = f.readline() if line == '': break parsha_name, start_ref = convertIntoRef(line) line = f.readline() parsha_name, end_ref = convertIntoRef(line) wholeRef = start_ref.to(end_ref).normal() parsha = ArrayMapNode() parsha.add_title(parsha_name, "en", primary=True) parsha.add_title(getHebrewParsha(parsha_name), "he", primary=True) parsha.key = parsha_name parsha.depth = 0 parsha.addressTypes = [] parsha.sectionNames = [] parsha.wholeRef = wholeRef parsha.refs = [] parshiot["nodes"].append(parsha.serialize()) for count, title in enumerate(title_eng): if title=='Devarim': continue f=open("perek_"+title+".txt", 'r') line = "nothing" first_one = "" last_one = "" refs_dict = {} current = 0 while line != '': prev_line = line line = f.readline() if line == '': break start_perek, start_ref = convertIntoRef(line) if prev_line == "nothing": first_one = (start_perek, start_ref) line = f.readline() end_perek, end_ref = convertIntoRef(line) last_one = (end_perek, end_ref) if start_perek == end_perek: refs_dict[start_perek] = start_ref.to(end_ref).normal() refs = [] for i in range(int(last_one[0])): if str(i+1) in refs_dict: refs.append(refs_dict[str(i+1)]) else: refs.append("") whole_ref = first_one[1].to(last_one[1]).normal() chumash = ArrayMapNode() chumash.add_title(title_heb[count], "he", primary=True) chumash.add_title(title, "en", primary=True) chumash.key = title chumash.addressTypes = ["Integer"] chumash.sectionNames = ["Chapter"] chumash.depth = 1 chumash.wholeRef = whole_ref chumash.refs = refs chumash.validate() perakim["nodes"].append(chumash.serialize()) f.close() root = JaggedArrayNode() root.key = "yalkut_on_nach" root.add_title("Yalkut Shimoni on Nach", "en", primary=True) root.add_title(u"""ילקות שמעוני על נ״ח""", "he", primary=True) root.depth = 2 root.sectionNames = ["Remez", "Paragraph"] root.heSectionNames = [u"רמז", u"פסקה"] root.addressTypes = ["Integer", "Integer"] index = { "title": "Yalkut Shimoni on Nach", "categories": ["Midrash"], "alt_structs": {"Parsha": parshiot, "Chapters": perakim}, "default_struct": "Remez", "schema": root.serialize() } post_index(index)

[ "skaplan@brandeis.edu" ]

skaplan@brandeis.edu

5167d45c33d996d136141fa7758a62e1f72334c7

8a2f5982c90c205cfee8f8fdce264a930c1b3749

/acoustics/standards/iso_1996_1_2003.py

266bc5cfdd490432fa7c696a757a75053959407c

[ "BSD-3-Clause", "Python-2.0", "LicenseRef-scancode-unknown-license-reference" ]

permissive

AlanLeJie/python-acoustics

05dde3ba6b7cf07265f5186f3742bb22f01fa1bb

af72e7f88003f0bba06934ea38c98e8993c4a6c6

refs/heads/master

2023-08-28T18:41:08.924307

2020-08-18T21:37:14

2021-10-26T12:24:40

444,331,803

1

0

BSD-3-Clause

2022-01-04T07:52:28

null

UTF-8

Python

false

1,313

py

""" ISO 1996-1:2003 =============== ISO 1996-1:2003 defines the basic quantities to be used for the description of noise in community environments and describes basic assessment procedures. It also specifies methods to assess environmental noise and gives guidance on predicting the potential annoyance response of a community to long-term exposure from various types of environmental noises. The sound sources can be separate or in various combinations. Application of the method to predict annoyance response is limited to areas where people reside and to related long-term land uses. """ import numpy as np def composite_rating_level(levels, hours, adjustment): """Composite rating level. :params levels: Level per period. :params hours: Amount of hours per period. :params adjustment: Adjustment per period. Composite whole-day rating levels are calculated as .. math:: L_R = 10 \\log{\\left[ \\sum_i \\frac{d_i}{24} 10^{(L_i+K_i)/10} \\right]} where :math:`i` is a period. See equation 6 and 7 of the standard. .. note:: Summation is done over the last axis. """ levels = np.asarray(levels) hours = np.asarray(hours) adjustment = np.asarray(adjustment) return 10.0 * np.log10((hours / 24.0 * 10.0**((levels + adjustment) / 10.0)).sum(axis=-1))

[ "fridh@fridh.nl" ]

fridh@fridh.nl

c2506960988c3521a7ee66ffa6b3e0b8285d7800

741ee09b8b73187fab06ecc1f07f46a6ba77e85c

/AutonomousSourceCode/data/raw/sort/02e9654d-b2b6-4400-b461-b0237b1385b4__selection_sort.py

32b8579c493ef2d06cb99bcee9dee400f3b1157d

[]

no_license

erickmiller/AutomatousSourceCode

fbe8c8fbf215430a87a8e80d0479eb9c8807accb

44ee2fb9ac970acf7389e5da35b930d076f2c530

refs/heads/master

2021-05-24T01:12:53.154621

2020-11-20T23:50:11

60,889,742

6

1

null

UTF-8

Python

false

822

py

from ds import arrays import sys from profile import profile @profile def sort(a): selection_sort(a,0,len(a)) def selection_sort(a,start,length): for i in xrange(start+1,start+length): key = a[i] j = i while(j>start and a[j-1]>key): a[j] = a[j-1] j -= 1 a[j] = key def main(): a = arrays.make(sys.argv) sort(a) return a if __name__=="__main__": main() ########################################tests######################################## def assert_sorted(a,from_index,length): selection_sort(a, from_index, length) for i in xrange(from_index, from_index + length - 1): assert a[i]<=a[i+1] def should_partially_sort(): assert_sorted([30,20,10,5,3,2,4,1,-4,-5],3,5) assert_sorted(arrays.array(50,False),10,20)

[ "erickmiller@gmail.com" ]

erickmiller@gmail.com

74e26e09eea6b1c02032bef6283506cea981f66f

5b11be48f06b6779fe073deb90dde14659543367

/coloredlogs/tests.py

f160d525e80fffe8de65f5b542bdc121101ea1e4

[ "MIT" ]

permissive

davliu/python-coloredlogs

03a612a6d6dd72255d7cee98386bf74f7ed5a204

549decbfde404b475cb772e86bdb5091f9f1baff

refs/heads/master

2020-05-20T18:31:58.680478

2015-06-02T19:03:23

null

0

null

UTF-8

Python

false

6,045

py

# Automated tests for the `coloredlogs' package. # # Author: Peter Odding <peter@peterodding.com> # Last Change: May 27, 2015 # URL: http://coloredlogs.readthedocs.org # Standard library modules. import logging import random import re import string import unittest # External dependencies. from humanfriendly.terminal import ansi_wrap # The module we're testing. import coloredlogs import coloredlogs.converter # External test dependency required to test support for custom log levels. import verboselogs # Compatibility with Python 2 and 3. try: # Python 2. from StringIO import StringIO except ImportError: # Python 3. from io import StringIO # Compiled regular expression that matches a single line of output produced by # ColoredStreamHandler (does not include matching of ANSI escape sequences). PLAIN_TEXT_PATTERN = re.compile(r''' (?P<date> \d{4}-\d{2}-\d{2} ) \s (?P<time> \d{2}:\d{2}:\d{2} ) \s (?P<hostname> \S+ ) \s (?P<logger_name> \w+ ) \[ (?P<process_id> \d+ ) \] \s (?P<severity> [A-Z]+ ) \s (?P<message> .* ) ''', re.VERBOSE) class ColoredLogsTestCase(unittest.TestCase): def setUp(self): """Start each test from a known state.""" # Reset global state. coloredlogs.install() coloredlogs.set_level(logging.INFO) # Reset local state. self.stream = StringIO() self.handler = coloredlogs.ColoredStreamHandler(stream=self.stream, isatty=False) self.logger_name = ''.join(random.choice(string.ascii_letters) for i in range(25)) self.logger = verboselogs.VerboseLogger(self.logger_name) self.logger.addHandler(self.handler) def test_is_verbose(self): """Make sure is_verbose() does what it should :-).""" assert coloredlogs.root_handler.level == logging.INFO assert not coloredlogs.is_verbose() coloredlogs.set_level(logging.VERBOSE) assert coloredlogs.is_verbose() def test_increase_verbosity(self): """Make sure increase_verbosity() respects default and custom levels.""" assert coloredlogs.root_handler.level == logging.INFO coloredlogs.increase_verbosity() assert coloredlogs.root_handler.level == logging.VERBOSE coloredlogs.increase_verbosity() assert coloredlogs.root_handler.level == logging.DEBUG coloredlogs.increase_verbosity() assert coloredlogs.root_handler.level == logging.NOTSET coloredlogs.increase_verbosity() assert coloredlogs.root_handler.level == logging.NOTSET def test_decrease_verbosity(self): """Make sure decrease_verbosity() respects default and custom levels.""" assert coloredlogs.root_handler.level == logging.INFO coloredlogs.decrease_verbosity() assert coloredlogs.root_handler.level == logging.WARNING coloredlogs.decrease_verbosity() assert coloredlogs.root_handler.level == logging.ERROR coloredlogs.decrease_verbosity() assert coloredlogs.root_handler.level == logging.CRITICAL coloredlogs.decrease_verbosity() assert coloredlogs.root_handler.level == logging.CRITICAL def test_level_discovery(self): """Make sure find_defined_levels() always reports the levels defined in Python's standard library.""" for number in (0, 10, 20, 30, 40, 50): assert number in coloredlogs.find_defined_levels() def test_missing_isatty_method(self): """Make sure ColoredStreamHandler() doesn't break because of a missing isatty() method.""" # This should not raise any exceptions in the constructor. coloredlogs.ColoredStreamHandler(stream=object()) def test_non_string_messages(self): """Make sure ColoredStreamHandler() doesn't break because of non-string messages.""" # This should not raise any exceptions; all of these values can be cast to strings. for value in (True, False, 0, 42, (), []): self.logger.info(value) def test_plain_text_output_format(self): """Inspect the plain text output of coloredlogs.""" # Test that filtering on severity works. self.handler.level = logging.INFO self.logger.debug("No one should see this message.") assert len(self.stream.getvalue().strip()) == 0 # Test that the default output format looks okay in plain text. self.handler.level = logging.DEBUG for method, severity in ((self.logger.debug, 'DEBUG'), (self.logger.info, 'INFO'), (self.logger.verbose, 'VERBOSE'), (self.logger.warning, 'WARN'), (self.logger.error, 'ERROR'), (self.logger.critical, 'CRITICAL')): # Prepare the text. text = "This is a message with severity %r." % severity.lower() # Log the message with the given severity. method(text) # Get the line of output generated by the handler. output = self.stream.getvalue() lines = output.splitlines() last_line = lines[-1] assert text in last_line assert severity in last_line assert PLAIN_TEXT_PATTERN.match(last_line) def test_html_conversion(self): ansi_encoded_text = 'I like %s - www.eelstheband.com' % ansi_wrap('birds', bold=True, color='blue') assert ansi_encoded_text == 'I like \x1b[1;34mbirds\x1b[0m - www.eelstheband.com' html_encoded_text = coloredlogs.converter.convert(ansi_encoded_text) assert html_encoded_text == 'I like <span style="font-weight: bold; color: blue;">birds</span> - <a href="http://www.eelstheband.com" style="color: inherit;">www.eelstheband.com</a>' def test_output_interception(self): expected_output = 'testing, 1, 2, 3 ..' assert coloredlogs.converter.capture(['sh', '-c', 'echo -n %s' % expected_output]) == expected_output

[ "peter@peterodding.com" ]

peter@peterodding.com

49a15a9cea2349452b2a8d4b6d3320a51ee31a06

cd4f28ff0efa74889c4db8e91fb2caaebe37d592

/data.py

4fe388fae73f36ff04095a522803be9981dd224a

[]

no_license

quirell/CSOBO

fd59f4fac0f9f38c32afb7277d6a4c1ecc59a8ea

73a98374cbf21920cecc9b19f77aee1624339769

refs/heads/master

2021-01-13T02:06:14.489103

2015-05-24T00:39:16

33,379,478

0

null

UTF-8

Python

false

2,948

py

__author__ = 'quirell' import os import re class TestCase: """ fullname - nazwa przypadku testowego testname - nazwa grupy do ktorej przypadek testowy nalezy, wiecej tu: http://anjos.mgi.polymtl.ca/qaplib/inst.html value - najlepsza (minimalna) wartosc rozwiazania solution - permutacja dla ktorej rozwiazanie przyjmuje najmniejsza wartosc distance, flow - wiadomo """ datapath = "" solutionspath = "" def __init__(self,name): self.fullname = name self.testname = re.match(r"([a-zA-Z]+).*",name).group(1) self.value = self.flow = self.distance = self.solution = None self.size = 0 def load(self): with open(TestCase.datapath + "/" + self.fullname + ".dat") as f: self.size = int(f.readline()) line = "\n" while line == "\n": line = f.readline() flow = [] for _ in xrange(self.size): flow.append([int(i) for i in line.split()]) while len(flow[-1]) != self.size: line = f.readline() flow[-1].extend([int(i) for i in line.split()]) line = f.readline() # line = "\n" while line == "\n": line = f.readline() distance = [] for _ in xrange(self.size): distance.append([int(i) for i in line.split()]) while len(distance[-1]) != self.size: line = f.readline() distance[-1].extend([int(i) for i in line.split()]) line = f.readline() solution = None if os.path.isfile(TestCase.solutionspath + "/" + self.fullname + ".sln"): with open(TestCase.solutionspath + "/" + self.fullname + ".sln") as f: line = f.readline() _, self.value = line.split() self.value = int(self.value) solution = [] for line in f: if "," in line: solution.extend([int(i.strip()) for i in line.split(",") if i.strip().isdigit()]) else: solution.extend([int(i.strip()) for i in line.split()]) self.flow = flow self.distance = distance if solution: self.solution = [i-1 for i in solution] def solutionavailable(self): return self.solution is not None def __str__(self): return self.fullname + " size: "+self.size+" value: "+self.value class Data: def __init__(self): self.datapath = "data" self.solutionspath = "solutions" TestCase.datapath = self.datapath TestCase.solutionspath = self.solutionspath def gettestcases(self): testcases = [] for filename in os.listdir(self.datapath): testcases.append(TestCase(filename[:-4])) return testcases

[ "=" ]

=

746cf426cb0daad0ecbfe251adf903b1597644cb

01b8229a1adbc8149e4226c81e31e56e0598b87b

/python/emp.py

8904efc26c20d0c856d6e55dda26f62c425d2f7a

[]

no_license

Amel294/amel

660f4cbd16f58d89a624bc90beeb791d239c6959

e54fd091a4bff436fe94a9901ca9b7c189b6824d

refs/heads/master

2023-05-10T16:56:54.039667

2023-05-08T16:57:18

160,795,270

0

null

UTF-8

Python

false

334

py

class employee: def add(self): self.name=raw_input('\nenter employee name:\t') self.nuber=input('\nemployee number:\t') self.salary=input('\nenter salary:\t') def show(self): print('\nname=',self.name,'\n') print('e number=',self.nuber,'\n') print('salary=',self.salary,'\n') x=employee() x.add() x.show()

[ "amel294@gmail.com" ]

amel294@gmail.com

bebb96c64a6feaa14c97cbda198522f712b111c1

d525935af3c80584fb2175623591a1fc86349db5

/Problems/Process integer input/task.py

929699ff539661399dfca3f35156baba73cba1c6

[]

no_license

TonyNewbie/CoffeeMachine

63822ffdec8570166ebf44c0ffe51bfa14d33810

319c41189ede6a2e6e33bd15ae675101c3377b62

refs/heads/master

2022-04-22T13:23:47.904126

2020-04-26T07:25:44

258,960,677

0

null

UTF-8

Python

false

153

py

number = int(input()) while number < 101: if number < 10: number = int(input()) continue print(number) number = int(input())

[ "prostomaster90@gmail.com" ]

prostomaster90@gmail.com

8bd8d6553e25d404d1919bb14a246ace10a097c8

a1a57977131ea917a3f3094dae4a3d18846103c0

/tests_auto/2d/quad4/axialdisp_gendb.py

d81640af303b4b9322f9a47bbcf8322f0d52db21

[ "MIT" ]

permissive

rwalkerlewis/pylith

cef02d5543e99a3e778a1c530967e6b5f1d5dcba

8d0170324d3fcdc5e6c4281759c680faa5dd8d38

refs/heads/master

2023-08-24T18:27:30.877550

2020-08-05T16:37:28

154,047,591

0

MIT

2018-10-21T20:05:59

null

UTF-8

Python

false

2,319

py

#!/usr/bin/env python # # ---------------------------------------------------------------------- # # Brad T. Aagaard, U.S. Geological Survey # Charles A. Williams, GNS Science # Matthew G. Knepley, University of Chicago # # This code was developed as part of the Computational Infrastructure # for Geodynamics (http://geodynamics.org). # # Copyright (c) 2010-2017 University of California, Davis # # See COPYING for license information. # # ---------------------------------------------------------------------- # ## @file tests/2d/quad4/axialdisp_gendb.py ## ## @brief Python script to generate spatial database with displacement ## boundary conditions for the axial displacement test. import numpy class GenerateDB(object): """ Python object to generate spatial database with displacement boundary conditions for the axial displacement test. """ def __init__(self): """ Constructor. """ return def run(self): """ Generate the database. """ # Domain x = numpy.arange(-4000.0, 4000.1, 1000.0) y = numpy.arange(-4000.0, 4000.1, 1000.0) npts = x.shape[0] xx = x * numpy.ones( (npts, 1), dtype=numpy.float64) yy = y * numpy.ones( (npts, 1), dtype=numpy.float64) xy = numpy.zeros( (npts**2, 2), dtype=numpy.float64) xy[:,0] = numpy.ravel(xx) xy[:,1] = numpy.ravel(numpy.transpose(yy)) from axialdisp_soln import AnalyticalSoln soln = AnalyticalSoln() disp = soln.displacement(xy) from spatialdata.geocoords.CSCart import CSCart cs = CSCart() cs.inventory.spaceDim = 2 cs._configure() data = {'points': xy, 'coordsys': cs, 'data_dim': 2, 'values': [{'name': "displacement-x", 'units': "m", 'data': numpy.ravel(disp[0,:,0])}, {'name': "displacement-y", 'units': "m", 'data': numpy.ravel(disp[0,:,1])}]} from spatialdata.spatialdb.SimpleIOAscii import SimpleIOAscii io = SimpleIOAscii() io.inventory.filename = "axial_disp.spatialdb" io._configure() io.write(data) return # ====================================================================== if __name__ == "__main__": app = GenerateDB() app.run() # End of file

[ "baagaard@usgs.gov" ]

baagaard@usgs.gov

1e175f5fbd461cacef895e6d82085207e7b62938

02ea99ea65d4768781b59ac97082fa7e1763711c

/neural_structured_learning/estimator/adversarial_regularization.py

a63a7ad858f2c30b8260beef2ba03ee89b88acf5

[ "Apache-2.0" ]

permissive

Nzteb/neural-structured-learning

cad8a94b7b7d0d77eb0d0dca584398d749ff4ca6

0d50227f01556b1cebbd841496f5d1c9c4ef4a61

refs/heads/master

2022-11-15T22:10:32.112476

2020-07-09T00:13:09

2020-07-09T00:13:37

null

0

null

UTF-8

Python

false

6,326

py

# Copyright 2019 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """A wrapper function to enable adversarial regularization to an Estimator.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import functools import inspect import neural_structured_learning.configs as nsl_configs import neural_structured_learning.lib as nsl_lib import tensorflow as tf def add_adversarial_regularization(estimator, optimizer_fn=None, adv_config=None): """Adds adversarial regularization to a `tf.estimator.Estimator`. The returned estimator will include the adversarial loss as a regularization term in its training objective, and will be trained using the optimizer provided by `optimizer_fn`. `optimizer_fn` (along with the hyperparameters) should be set to the same one used in the base `estimator`. If `optimizer_fn` is not set, a default optimizer `tf.train.AdagradOptimizer` with `learning_rate=0.05` will be used. Args: estimator: A `tf.estimator.Estimator` object, the base model. optimizer_fn: A function that accepts no arguments and returns an instance of `tf.train.Optimizer`. This optimizer (instead of the one used in `estimator`) will be used to train the model. If not specified, default to `tf.train.AdagradOptimizer` with `learning_rate=0.05`. adv_config: An instance of `nsl.configs.AdvRegConfig` that specifies various hyperparameters for adversarial regularization. Returns: A modified `tf.estimator.Estimator` object with adversarial regularization incorporated into its loss. """ if not adv_config: adv_config = nsl_configs.AdvRegConfig() base_model_fn = estimator._model_fn # pylint: disable=protected-access try: base_model_fn_args = inspect.signature(base_model_fn).parameters.keys() except AttributeError: # For Python 2 compatibility base_model_fn_args = inspect.getargspec(base_model_fn).args # pylint: disable=deprecated-method def adv_model_fn(features, labels, mode, params=None, config=None): """The adversarial-regularized model_fn. Args: features: This is the first item returned from the `input_fn` passed to `train`, `evaluate`, and `predict`. This should be a single `tf.Tensor` or `dict` of same. labels: This is the second item returned from the `input_fn` passed to `train`, `evaluate`, and `predict`. This should be a single `tf.Tensor` or dict of same (for multi-head models). If mode is `tf.estimator.ModeKeys.PREDICT`, `labels=None` will be passed. If the `model_fn`'s signature does not accept `mode`, the `model_fn` must still be able to handle `labels=None`. mode: Optional. Specifies if this is training, evaluation, or prediction. See `tf.estimator.ModeKeys`. params: Optional `dict` of hyperparameters. Will receive what is passed to Estimator in the `params` parameter. This allows users to configure Estimators from hyper parameter tuning. config: Optional `estimator.RunConfig` object. Will receive what is passed to Estimator as its `config` parameter, or a default value. Allows setting up things in the model_fn based on configuration such as `num_ps_replicas`, or `model_dir`. Unused currently. Returns: A `tf.estimator.EstimatorSpec` with adversarial regularization. """ # Parameters 'params' and 'config' are optional. If they are not passed, # then it is possible for base_model_fn not to accept these arguments. # See documentation for tf.estimator.Estimator for additional context. kwargs = {'mode': mode} if 'params' in base_model_fn_args: kwargs['params'] = params if 'config' in base_model_fn_args: kwargs['config'] = config base_fn = functools.partial(base_model_fn, **kwargs) # Uses the same variable scope for calculating the original objective and # adversarial regularization. with tf.compat.v1.variable_scope(tf.compat.v1.get_variable_scope(), reuse=tf.compat.v1.AUTO_REUSE, auxiliary_name_scope=False): original_spec = base_fn(features, labels) # Adversarial regularization only happens in training. if mode != tf.estimator.ModeKeys.TRAIN: return original_spec adv_neighbor, _ = nsl_lib.gen_adv_neighbor( features, original_spec.loss, adv_config.adv_neighbor_config, # The pgd_model_fn is a dummy identity function since loss is # directly available from spec_fn. pgd_model_fn=lambda features: features, pgd_loss_fn=lambda labels, features: base_fn(features, labels).loss, pgd_labels=labels) # Runs the base model again to compute loss on adv_neighbor. adv_spec = base_fn(adv_neighbor, labels) final_loss = original_spec.loss + adv_config.multiplier * adv_spec.loss if not optimizer_fn: # Default to the Adagrad optimizer, the same as canned DNNEstimator. optimizer = tf.train.AdagradOptimizer(learning_rate=0.05) else: optimizer = optimizer_fn() train_op = optimizer.minimize( loss=final_loss, global_step=tf.compat.v1.train.get_global_step()) update_ops = tf.compat.v1.get_collection( tf.compat.v1.GraphKeys.UPDATE_OPS) if update_ops: train_op = tf.group(train_op, *update_ops) return original_spec._replace(loss=final_loss, train_op=train_op) # Replaces the model_fn while keeps other fields/methods in the estimator. estimator._model_fn = adv_model_fn # pylint: disable=protected-access return estimator

[ "tensorflow.copybara@gmail.com" ]

tensorflow.copybara@gmail.com

6f0e144c9f2150d6ed2b247269a15962705f55d8

f98c9dea0e212be5c7bc3161499e5633383bd4d7

/zmq/zmq_client.py

a27214a3bfe54b37c5d0b7c49f3ab8e11e63d9e0

[ "MIT" ]

permissive

ysoftman/test_code

dddb5bee3420977bfa335320a09d66e5984403f5

0bf6307073081eeb1d654a1eb5efde44a0bdfe1e

refs/heads/master

2023-08-17T05:45:49.716829

2023-08-16T05:00:09

108,200,568

4

0

MIT

2023-03-15T04:23:10

2017-10-25T00:49:26

C++

UTF-8

Python

false

713

py

#-*- coding: utf-8 -*- # 20160422 ysoftman # pyzmq (python3.x) client import zmq import sys def send_req(ip, port): context = zmq.Context() socket = context.socket(zmq.REQ) # socket.setsockopt(zmq.REQ, b'') socket.connect("tcp://%s:%s" % (ip, port)) # python 3 에서 기본 인코딩이 유니코드 # send 함스는 유니코드를 사용할 수 없어, byte 형태로 만든다. data = b'hello' for i in range(10): socket.send(data) print("send %s to server. [%d]" % (data, i)) reply = socket.recv() print("reply %s from server.[%d]" % (reply, i)) if __name__ == "__main__": print("start testing...") send_req("127.0.0.1", "55555")

[ "ysoftman@gmail.com" ]

ysoftman@gmail.com

7f0537ded18f3ab59f3f0455f9f3074597b23440

377e3a552fb807febc18ce036af77edbce93ca19

/binary trees/inorder_traversal_DFS.py

47831f96111d76a9cebf1a030c565db26ac4a083

[]

no_license

souravs17031999/100dayscodingchallenge

940eb9b6d6037be4fc0dd5605f9f808614085bd9

d05966f3e6875a5ec5a8870b9d2627be570d18d9

refs/heads/master

2022-10-29T11:05:46.762554

2022-09-28T13:04:32

215,993,823

44

12

null

2022-08-18T14:58:50

2019-10-18T09:55:03

Python

UTF-8

Python

false

2,714

py

# Program for inorder traversal for a binary tree # -------------------------------- # As we know inorder traversal means, Left-Node-Right # We can take example for follwoing tree and visualize stack call : # 1 # / \ # 2 3 # / \ # 4 5 # # RECURSIVE APPROACH # -------------------------------- # TIME : 0(N), SPACE : NOT CONSTANT, DUE TO RECURSIVE CALLS. # WE should also try to write iterative solution, because there might # be some case where stack recursion depth limit is exceeded due to not # enough memory available or due to system limit on recursion calls. # --------------------------------------- # ITERATIVE SOLTUION : #Push the current node to S and set current = current->left until current is NULL # If current is NULL and stack is not empty then # * Pop the top item from stack. # * Print the popped item, set current = popped_item->right # * Go to step 3. # If current is NULL and stack is empty then we are done. # --------------------------------------------- # TIME : 0(N), SPACE : 0(N) WHERE N IS THE NUMBER OF NODES IN THE TREE. # ---------------------------------------------- # we can also optimized more on space complexity part by not using any # stack or recursion, named as "MORRIS TRAVERSAL" which is described in # MORRIS_traversal.py in a separate program. # ---------------------------------------------- class Node: def __init__(self, val): self.data = val self.left = None self.right = None # inorder recursive def inorder_rec(root): if root == None: return inorder_rec(root.left) print(root.data, end = " ") inorder_rec(root.right) # ITERATIVE SOLUTION : from collections import deque def inorder_itr(root): if root == None: return stack = deque([]) ptr = root while True: # this will be true everytimee until ptr.left becomes None, # that means all the left ones will be on the stack firstly. if ptr: stack.append(ptr) ptr = ptr.left # now when above fails, then we need to pop the top of stack # and print it, also make current ptr to ptr.right to traverse # for right subtree elif stack: ptr = stack.pop() print(ptr.data, end = " ") ptr = ptr.right # now if current ptr is also None and stack is also empty, # then we need to move out of loop. else: break # driver test function if __name__ == '__main__': root = Node(1) root.left = Node(2) root.right = Node(3) root.left.left = Node(4) root.left.right = Node(5) #inorder_rec(root) inorder_itr(root)

[ "souravs_1999@rediffmail.com" ]

souravs_1999@rediffmail.com

da5ef56bfccc88c74e51c8cf0376e38e3a3ca319

7626a8371c7a847f93bdae5e1d6e03ee9667c3ba

/print/users/migrations/0001_initial.py

08083d447c75319b2a232ce671351aac48b5e516

[]

no_license

zzyzx4/sp

52c815fd115b4605942baa73687838f64cd41864

90c7a90b3de27af674422e2c8892bad5ba7891e8

refs/heads/master

2020-05-23T21:20:28.166932

2019-07-19T11:56:49

186,950,380

0

null

UTF-8

Python

false

777

py

# Generated by Django 2.2.2 on 2019-06-24 15:40 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), ] operations = [ migrations.CreateModel( name='Profile', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('image', models.ImageField(default='default.jpg', upload_to='profile_pics')), ('user', models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

[ "you@example.com" ]

you@example.com

946f6acb38c734fdff7ed61463b00a60f7de3399

f0316e656767cf505b32c83eef4df13bb9f6b60c

/Kattis/qaly.py

86b1b75314997d2f525dc10e31ebf5f2bd66f855

[]

no_license

AkshdeepSharma/Classroom

70ec46b35fab5fc4a9d2eac430659d7dafba93da

4e55799466c101c736de6c7e07d716ff147deb83

refs/heads/master

2022-06-13T18:14:03.236503

2022-05-17T20:16:28

94,828,359

1

0

null

UTF-8

Python

false

141

py

N = int(input()) qaly = 0 for i in range(N): nums = input().split(" ") qaly += float(nums[0]) * float(nums[1]) print(round(qaly, 3))

[ "akshdeep.sharma1@gmail.com" ]

akshdeep.sharma1@gmail.com

a332e92186cd5002d1095263b0a5abaae4af5d37

3c27b86f0165ab24e6b04d505e8471e032594f0b

/pythonAnimations/pyOpenGLChess/engineDirectory/oglc-env/lib/python2.7/site-packages/OpenGL/raw/GLES1/OES/texture_cube_map.py

1f616ca628a9790612c0acccc4ae8f17355fac0e

[ "LicenseRef-scancode-warranty-disclaimer", "GPL-1.0-or-later", "LicenseRef-scancode-other-copyleft", "LGPL-2.1-or-later", "GPL-3.0-only", "LGPL-2.0-or-later", "GPL-3.0-or-later", "MIT" ]

permissive

alexus37/AugmentedRealityChess

8b9ccdfffc8aee93a86a44b8ef53c034ec6a10d1

7f600ad153270feff12aa7aa86d7ed0a49ebc71c

refs/heads/master

2020-12-24T13:29:21.967833

2020-02-27T09:38:50

31,264,034

1

MIT

2020-02-27T09:38:52

2015-02-24T14:36:34

Python

UTF-8

Python

false

2,394

py

'''Autogenerated by xml_generate script, do not edit!''' from OpenGL import platform as _p, arrays # Code generation uses this from OpenGL.raw.GLES1 import _types as _cs # End users want this... from OpenGL.raw.GLES1._types import * from OpenGL.raw.GLES1 import _errors from OpenGL.constant import Constant as _C import ctypes _EXTENSION_NAME = 'GLES1_OES_texture_cube_map' def _f( function ): return _p.createFunction( function,_p.PLATFORM.GLES1,'GLES1_OES_texture_cube_map',error_checker=_errors._error_checker) GL_MAX_CUBE_MAP_TEXTURE_SIZE_OES=_C('GL_MAX_CUBE_MAP_TEXTURE_SIZE_OES',0x851C) GL_NORMAL_MAP_OES=_C('GL_NORMAL_MAP_OES',0x8511) GL_REFLECTION_MAP_OES=_C('GL_REFLECTION_MAP_OES',0x8512) GL_TEXTURE_BINDING_CUBE_MAP_OES=_C('GL_TEXTURE_BINDING_CUBE_MAP_OES',0x8514) GL_TEXTURE_CUBE_MAP_NEGATIVE_X_OES=_C('GL_TEXTURE_CUBE_MAP_NEGATIVE_X_OES',0x8516) GL_TEXTURE_CUBE_MAP_NEGATIVE_Y_OES=_C('GL_TEXTURE_CUBE_MAP_NEGATIVE_Y_OES',0x8518) GL_TEXTURE_CUBE_MAP_NEGATIVE_Z_OES=_C('GL_TEXTURE_CUBE_MAP_NEGATIVE_Z_OES',0x851A) GL_TEXTURE_CUBE_MAP_OES=_C('GL_TEXTURE_CUBE_MAP_OES',0x8513) GL_TEXTURE_CUBE_MAP_POSITIVE_X_OES=_C('GL_TEXTURE_CUBE_MAP_POSITIVE_X_OES',0x8515) GL_TEXTURE_CUBE_MAP_POSITIVE_Y_OES=_C('GL_TEXTURE_CUBE_MAP_POSITIVE_Y_OES',0x8517) GL_TEXTURE_CUBE_MAP_POSITIVE_Z_OES=_C('GL_TEXTURE_CUBE_MAP_POSITIVE_Z_OES',0x8519) GL_TEXTURE_GEN_MODE_OES=_C('GL_TEXTURE_GEN_MODE_OES',0x2500) GL_TEXTURE_GEN_STR_OES=_C('GL_TEXTURE_GEN_STR_OES',0x8D60) @_f @_p.types(None,_cs.GLenum,_cs.GLenum,arrays.GLfloatArray) def glGetTexGenfvOES(coord,pname,params):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,arrays.GLintArray) def glGetTexGenivOES(coord,pname,params):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,ctypes.POINTER(_cs.GLfixed)) def glGetTexGenxvOES(coord,pname,params):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,_cs.GLfloat) def glTexGenfOES(coord,pname,param):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,arrays.GLfloatArray) def glTexGenfvOES(coord,pname,params):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,_cs.GLint) def glTexGeniOES(coord,pname,param):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,arrays.GLintArray) def glTexGenivOES(coord,pname,params):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,_cs.GLfixed) def glTexGenxOES(coord,pname,param):pass @_f @_p.types(None,_cs.GLenum,_cs.GLenum,ctypes.POINTER(_cs.GLfixed)) def glTexGenxvOES(coord,pname,params):pass

[ "alexlelidis@gmx.de" ]

alexlelidis@gmx.de

fc32d33d92acf211a927ee9591a9c2e2c794716f

faa83048d2bb62c27f030942f3f038f87637c293

/indico/core/oauth/protector.py

29693821d8a79e3bc2dcaeb25d629331dcedddbf

[ "MIT" ]

permissive

janschill/indico

f79536db43afaf631449fef5119069af2938e76d

068a947446eb624308d6264e34a4061807e6ff12

refs/heads/master

2023-06-08T07:32:33.007683

2021-06-18T12:42:03

339,700,154

0

MIT

2021-06-18T12:42:04

2021-02-17T11:22:48

Python

UTF-8

Python

false

3,105

py

# This file is part of Indico. # Copyright (C) 2002 - 2021 CERN # # Indico is free software; you can redistribute it and/or # modify it under the terms of the MIT License; see the # LICENSE file for more details. import flask from authlib.integrations.flask_oauth2 import ResourceProtector from authlib.oauth2.rfc6750.validator import BearerTokenValidator from flask import after_this_request, jsonify from werkzeug.exceptions import HTTPException from indico.core.db import db from indico.core.oauth.models.applications import SystemAppType from indico.core.oauth.models.tokens import OAuthToken from indico.core.oauth.util import query_token from indico.util.date_time import now_utc class IndicoAuthlibHTTPError(HTTPException): def __init__(self, status_code, payload, headers): super().__init__(payload.get('error_description') or payload['error']) resp = jsonify(payload) resp.headers.update(headers) resp.status_code = status_code self.response = resp class IndicoResourceProtector(ResourceProtector): def raise_error_response(self, error): payload = dict(error.get_body()) headers = error.get_headers() raise IndicoAuthlibHTTPError(error.status_code, payload, headers) def parse_request_authorization(self, request): access_token_querystring = flask.request.args.get('access_token') if access_token_querystring and not request.headers.get('Authorization', '').lower().startswith('bearer '): validator = self.get_token_validator('legacy_qs') return validator, access_token_querystring return super().parse_request_authorization(request) class IndicoBearerTokenValidator(BearerTokenValidator): def authenticate_token(self, token_string): return query_token(token_string) def validate_token(self, token, scopes): super().validate_token(token, scopes) # if we get here, the token is valid so we can mark it as used at the end of the request # XXX: should we wait or do it just now? even if the request failed for some reason, the # token could be considered used, since it was valid and most likely used by a client who # expected to do something with it... token_id = token.id # avoid DetachedInstanceError in the callback @after_this_request def _update_last_use(response): with db.tmp_session() as sess: # do not modify `token` directly, it's attached to a different session! sess.query(OAuthToken).filter_by(id=token_id).update({OAuthToken.last_used_dt: now_utc()}) sess.commit() return response class IndicoLegacyQueryStringBearerTokenValidator(IndicoBearerTokenValidator): TOKEN_TYPE = 'legacy_qs' def authenticate_token(self, token_string): token = super().authenticate_token(token_string) if token and token.application.system_app_type == SystemAppType.checkin: # Only the checkin app is allowed to pass tokens insecurely via query string return token

[ "adrian.moennich@cern.ch" ]

adrian.moennich@cern.ch

78b44ed568709f7982622043bd51601faeed8ab8

4791bde7bb7275fc25480fdf0cd81d1a9450a50c

/accounts/views.py

2cd377f5f3cbd97f9432c0c428c386f474093f90

[]

no_license

VinneyJ/RU-I-tech-app

9692f0681dd704ce52c621b3d080d1a90fbe501b

dd15335f26a35d8e32477e7dd384f3a80351d25d

refs/heads/master

2020-05-02T21:04:17.773867

2019-03-28T13:25:18

178,209,692

0

null

UTF-8

Python

false

2,070

py

from django.shortcuts import render, redirect from django.contrib.auth.forms import AuthenticationForm from django.contrib.auth.decorators import login_required from django.contrib.auth import login, logout from accounts.form import UserRegisterForm, UserUpdateForm, ProfileUpdateForm from .models import Profile # Create your views here. def signup_view(request): if request.method == 'POST': form = UserRegisterForm(request.POST) if form.is_valid(): user = form.save() #log user in login(request, user) return redirect('articles:list') else: form=UserRegisterForm() return render(request, 'accounts/signup.html', {'form':form}) def login_view(request): if request.method == 'POST': form = AuthenticationForm(data=request.POST) if form.is_valid(): user = form.get_user() login(request,user) #log user in if 'next' in request.POST: return redirect(request.POST.get('next')) else: return redirect('articles:list') else: form = AuthenticationForm() return render(request, 'accounts/login.html', {'form':form}) @login_required def profile_view(request): if request.method == 'POST': u_form = UserUpdateForm(request.POST, instance=request.user) p_form = ProfileUpdateForm(request.POST, request.FILES, instance=request.user.profile) if u_form.is_valid and p_form.is_valid(): u_form.save() p_form.save() #ENTER MESSAGES HERE return redirect('accounts:profile') else: u_form = UserUpdateForm(instance=request.user) p_form = ProfileUpdateForm(instance=request.user.profile) return render(request, 'accounts/profile.html', {'u_form' : u_form, 'p_form' : p_form}) def logout_view(request): if request.method =='POST': logout(request) return redirect('articles:list')

[ "vincentjayden49@gmail.com" ]

vincentjayden49@gmail.com

86c0cb10d29d06dcf7aa7a311986ac1f5d219e7e

2420eab92b5d1ec2225d2eeb128a41e3c7b1ce38

/11/JackTonenizer.py

b7a45cc64a958be663d46d4e26cc25dc8127e138

[]

no_license

hokiepete/building-a-modern-computer-from-first-principles

f98549a5d32ff23d4eab3b089324e61dac22841a

bba0d437b10ba5b5f6861067b3a0ba4ac14ef447

refs/heads/master

2023-08-17T21:38:44.589836

2021-10-24T01:41:56

385,073,300

0

null

UTF-8

Python

false

5,155

py

# Main program that sets up and invokes the other modules import os KEYWORDS = set([ 'class','constructor','function','method','field','static','var','int','char','boolean', 'void','true','false','null','this','let','do','if','else','while','return' ]) SYMBOL = set([ '{','}','(',')','[',']','.',',',';','+','-','*','/','&','|','<','>','=','~' ]) SUBS = {'<':'<', '>': '>', '\'': '"', '\"': '"', '&': '&'} class JackTokenizer: def __init__(self, input_string): self.raw_string = input_string self.tokens = [] self.tagged_tokens = [] self.clean_lines() self.tokenize() self.tag_tokens() def clean_lines(self): lines = self.raw_string.split('\n') cleaned = [] IN_COMMENT = False for line in lines: if IN_COMMENT: if "*/" in line: IN_COMMENT = False cleaned_line = line.split('*/')[1].strip() else: continue elif '//' in line: cleaned_line = line.split('//')[0].strip() elif "//*" in line: if '*/' in line: pref, suff = line.split('//*') cleaned_line = pref.strip() + ' ' + suff.split('*/')[1].strip() else: IN_COMMENT = True cleaned_line = line.split('//*')[0].strip() elif "/*" in line: if '*/' in line: pref, suff = line.split('/*') cleaned_line = pref.strip() + ' ' + suff.split('*/')[1].strip() else: IN_COMMENT = True cleaned_line = line.split('/*')[0].strip() else: cleaned_line = line.strip() if cleaned_line and (not cleaned_line.isspace()): cleaned.append(cleaned_line) self.cleaned_string = ' '.join(cleaned) def tokenize(self): while self.cleaned_string: token = self.get_next_token() if token: self.tokens.append(token) def get_next_token(self): token = '' literal = False for i, char in enumerate(self.cleaned_string): if char in ['\'', "\""]: if literal: literal = False else: literal = True if not literal: if char == ' ': self.cleaned_string = self.cleaned_string[i+1:] return token if char in SYMBOL: if token: self.cleaned_string = self.cleaned_string[i:] return token else: self.cleaned_string = self.cleaned_string[i+1:] return char if token.isnumeric() and not char.isnumeric(): raise ValueError( f"Variable names cannot start with a numeric character. Please fix token beginning with {token + char}" ) token += char return token def tag_tokens(self): self.tagged_tokens.append('<tokens>') for token in self.tokens: if token in KEYWORDS: self.tagged_tokens.append(f"<keyword> {token} </keyword>") elif token in SUBS: self.tagged_tokens.append(f"<symbol> {SUBS[token]} </symbol>") elif token in SYMBOL: self.tagged_tokens.append(f"<symbol> {token} </symbol>") elif token[0] in ['\'', '\"']: self.tagged_tokens.append(f"<stringConstant> {token[1:-1]} </stringConstant>") elif token.isnumeric(): self.tagged_tokens.append(f"<integerConstant> {token} </integerConstant>") else: self.tagged_tokens.append(f"<identifier> {token} </identifier>") self.tagged_tokens.append('</tokens>') if __name__ == '__main__': srcpath = 'ArrayTest\Main.jack' if os.path.isdir(srcpath): # read and parse the system file # with open(srcpath + '\\Sys.vm', 'r') as file: # text = file.read() # get all the files in the directory minus the system file # and parse the files files = os.listdir(srcpath) for file in files: if file.endswith('.jack'): with open(srcpath + f'\\{file}', 'r') as f: text = f.read() analyzer = JackTokenizer(text) destfile = f'{srcpath}\\{file.replace(".jack", "T.xml")}' with open(destfile, 'w') as f: f.write('\n'.join(analyzer.tagged_tokens)+'\n') else: with open(srcpath, 'r') as file: text = file.read() analyzer = JackTokenizer(text) destfile = f'{srcpath.replace(".jack", "T.xml")}' with open(destfile, 'w') as f: f.write('\n'.join(analyzer.tagged_tokens)+'\n')

[ "pnolan1986@gmail.com" ]

pnolan1986@gmail.com

6a8158e71b678a31bafc2805c7a170059a1636e0

8528604d3231d86feada09465170220b892c1c35

/landlab/grid/warnings.py

f1b23dd50399188b1024ed1c35288a9fb622b4ba

[ "MIT" ]

permissive

ChristinaB/landlab

9780acbd5753741cd91c40dbc5d683b66f2481a6

82fd45d059dbe58728b074b024e46a1a10ce1e5c

refs/heads/master

2021-04-26T22:45:44.007416

2020-12-02T22:57:27

124,138,852

0

1

MIT

2020-12-02T22:57:28

2018-03-06T21:08:56

Python

UTF-8

Python

false

988

py

import os from ..core.messages import deprecation_message class DeprecatedSignature(DeprecationWarning): msg = "You are using a deprecated calling signature." def __init__(self, name, old=None, new=None): self._name = name self._old = old self._new = new if old: self._old = self._construct_call(name, self._old[0], self._old[1]) if new: self._new = self._construct_call(name, self._new[0], self._new[1]) @staticmethod def _construct_call(name, args, kwds): signature = ", ".join( [repr(arg) for arg in args] + ["{k}={v}".format(k=k, v=repr(v)) for k, v in kwds.items()] ) return "{name}({signature})".format(name=name, signature=signature) def __str__(self): if self._new: use = ">>> grid = {call}".format(call=self._new) else: use = None return os.linesep + deprecation_message(self.msg, use=use)

[ "mcflugen@gmail.com" ]

mcflugen@gmail.com

99a5ca707f3d8c2a1b8bca69fffae0e09c4debbb

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03007/s124226483.py

6a9358f63822c404d9005c20865e9e13e95ae0d6

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

1,008

py

def c_successive_subtraction(N, A): A.sort() maximum = A.pop() minimum = A.pop(0) # Aの要素のうち、最大のものと最小のものを分けて置いておく。 # それら以外の要素 a_k について、 # a_k が非負なら、最小のものから a_k を引くことで負の方向に大きくできる。 # a_k が負なら、最大のものから a_k を引くことで正の方向に大きくできる。 # 最後に最大のもの - 最小のものとすると、最後に残る整数を最大にできる。 operation = [] for a in A: if a >= 0: operation.append('{} {}'.format(minimum, a)) minimum -= a else: operation.append('{} {}'.format(maximum, a)) maximum -= a operation.append('{} {}'.format(maximum, minimum)) return str(maximum - minimum) + '\n' + '\n'.join(operation) N = int(input()) A = [int(i) for i in input().split()] print(c_successive_subtraction(N, A))

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

2c9a70b0cecef465d4b201e73b956ba6ebe213bf

d1969a22afb7adda791caa4edf464dad02b684c0

/apps/edu/urls.py

b7d0eac3b362ac6a5aee738851c571d6a27a6507

[ "MIT" ]

permissive

local-host-club/cms

11d4ea1105dabc6d0a60b935484b5f9eb2ec1da9

136fb075f11011ea77672b3468f69262a43eb500

refs/heads/master

2020-07-02T17:09:36.135855

2016-11-28T13:31:11

74,293,699

0

null

UTF-8

Python

false

1,036

py

"""cms URL Configuration """ from django.conf.urls import url from apps.edu import views urlpatterns = [ url(r'^curriculo/$', views.CompetenciaAreaList.as_view(), name='curriculo'), url(r'^competencia_area/add$', views.CompetenciaAreaCreateView.as_view(), name='competencia_area_add'), url(r'^competencia_area/(?P<pk>\d+)/$', views.CompetenciaAreaDetail.as_view(), name='competencia_area_detail'), url(r'^competencia/add$', views.CompetenciaCreateView.as_view(), name='competencia_add'), url(r'^indicador/add$', views.IndicadorCreateView.as_view(), name='indicador_add'), url(r'^nivel/add$', views.NivelCreateView.as_view(), name='nivel_add'), url(r'^nota/(?P<pk>\d+)/add$', views.NotaCreateView.as_view(), name='nota_add'), url(r'^evaluacion/add$', views.EvaluacionCreateView.as_view(), name='evaluacion_add'), url(r'^evaluacion/list$', views.EvaluacionListView.as_view(), name='evaluacion_list'), url(r'^evaluacion/(?P<pk>\d+)$', views.EvaluacionDetail.as_view(), name='evaluacion_detail'), ]

[ "jinchuika@gmail.com" ]

jinchuika@gmail.com

6c2852e49e135f9302519afe6ba267c820f0331f

ac5e52a3fc52dde58d208746cddabef2e378119e

/exps-gsn-edf/gsn-edf_ut=2.0_rd=0.5_rw=0.04_rn=4_u=0.075-0.35_p=harmonic-2/sched=RUN_trial=53/sched.py

4782c407067e60157e4904c483d2dc99938f2852

[]

no_license

ricardobtxr/experiment-scripts

1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1

7bcebff7ac2f2822423f211f1162cd017a18babb

refs/heads/master

2023-04-09T02:37:41.466794

2021-04-25T03:27:16

358,926,457

0

null

UTF-8

Python

false

175

py

-X FMLP -Q 0 -L 2 70 300 -X FMLP -Q 0 -L 2 60 200 -X FMLP -Q 1 -L 2 58 175 -X FMLP -Q 2 -L 2 55 175 -X FMLP -Q 3 -L 1 33 200 30 400 30 400 26 100 20 125 15 175

[ "ricardo.btxr@gmail.com" ]

ricardo.btxr@gmail.com

f9799d5d427629227541426eb2f76d39b9c7be55

06e2dd0aa78241edbe647a8b5ef075a90ee4a8b6

/97/holidays.py

719a5166b67dda66aa92ab9dfadacfa9422f242d

[]

no_license

StefanKaeser/pybites

a6a78b51039ab4792deb285dc799c6abf7bea6d5

9f839af4ef400786b7c28701c2241f310bb4422c

refs/heads/master

2020-08-23T11:28:03.172666

2020-06-15T15:37:14

216,606,021

0

null

UTF-8

Python

false

1,051

py

from collections import defaultdict import os from urllib.request import urlretrieve from bs4 import BeautifulSoup # prep data # tmp = os.getenv("TMP", "/tmp") tmp = os.path.curdir page = "us_holidays.html" holidays_page = os.path.join(tmp, page) urlretrieve(f"https://bites-data.s3.us-east-2.amazonaws.com/{page}", holidays_page) with open(holidays_page) as f: content = f.read() def get_us_bank_holidays(content=content): """Receive scraped html output, make a BS object, parse the bank holiday table (css class = list-table), and return a dict of keys -> months and values -> list of bank holidays""" soup = BeautifulSoup(content, "html.parser") holiday_table = soup.find("table", {"class": "list-table"}) months = [tag.string.split("-")[1] for tag in holiday_table.find_all("time")] holiday_names = [tag.string.strip() for tag in holiday_table.find_all("a")] holidays = defaultdict(list) for month, name in zip(months, holiday_names): holidays[month].append(name) return holidays

[ "stefan.kaeser7@gmail.com" ]

stefan.kaeser7@gmail.com

0381c9188731c7b9a643d7d35757c09a22da7724

f2ebfb99b0e6a07afba7e583f820737511a1a98e

/code/models/listener.py

53325f3801b8e3ba46209f53072932ee06991b75

[ "MIT" ]

permissive

jayelm/emergent-generalization

211c065d4829322792396ad6605dc51024e913cd

35b1d97a940826008cde13498aa75c233a7f454a

refs/heads/master

2023-08-27T00:25:32.988514

2021-09-29T04:47:22

373,944,198

14

1

null

UTF-8

Python

false

2,517

py

""" Listener models """ import torch import torch.nn as nn from . import rnn class CopyListener(nn.Module): def __init__(self, feat_model, message_size=100, dropout=0.2): super().__init__() self.feat_model = feat_model self.feat_size = feat_model.final_feat_dim self.dropout = nn.Dropout(p=dropout) self.message_size = message_size if self.message_size is None: self.bilinear = nn.Linear(self.feat_size, 1, bias=False) else: self.bilinear = nn.Linear(self.message_size, self.feat_size, bias=False) def embed_features(self, feats): batch_size = feats.shape[0] n_obj = feats.shape[1] rest = feats.shape[2:] feats_flat = feats.view(batch_size * n_obj, *rest) feats_emb_flat = self.feat_model(feats_flat) feats_emb = feats_emb_flat.unsqueeze(1).view(batch_size, n_obj, -1) feats_emb = self.dropout(feats_emb) return feats_emb def compare(self, feats_emb, message_enc): """ Compute dot products """ scores = torch.einsum("ijh,ih->ij", (feats_emb, message_enc)) return scores def forward(self, feats, message): # Embed features feats_emb = self.embed_features(feats) # Embed message if self.message_size is None: return self.bilinear(feats_emb).squeeze(2) else: message_bilinear = self.bilinear(message) return self.compare(feats_emb, message_bilinear) def reset_parameters(self): self.feat_model.reset_parameters() self.bilinear.reset_parameters() class Listener(CopyListener): def __init__(self, feat_model, embedding_module, **kwargs): super().__init__(feat_model, **kwargs) self.embedding = embedding_module self.lang_model = rnn.RNNEncoder(self.embedding, hidden_size=self.message_size) self.vocab_size = embedding_module.num_embeddings def forward(self, feats, lang, lang_length): # Embed features feats_emb = self.embed_features(feats) # Embed language lang_emb = self.lang_model(lang, lang_length) # Bilinear term: lang embedding space -> feature embedding space lang_bilinear = self.bilinear(lang_emb) return self.compare(feats_emb, lang_bilinear) def reset_parameters(self): super().reset_parameters() self.embedding.reset_parameters() self.lang_model.reset_parameters()

[ "6245103+jayelm@users.noreply.github.com" ]

6245103+jayelm@users.noreply.github.com

de99f451e82714b1c4644394330ee7044c740365

62cbf8dcd921feb309d79ad66767405ea27623ba

/python/boj/2667_boj_danji.py

34b79935b3fb77392d1a17aad2eb8c53ba322477

[]

no_license

woodg1207/APS

1d20f8b7c6d7a7f41e9920ec41ad0c435a881519

e49a6fb01e1a51213963cd58f13a1364833482f8

refs/heads/master

2023-06-13T21:41:28.114299

2021-06-21T04:17:19

288,982,972

0

null

UTF-8

Python

false

802

py

import sys; sys.stdin=open('s2667.txt','r') from collections import deque N = int(input()) arr = [list(map(int, input())) for _ in range(N)] dr = [1,0,-1,0] dc = [0,1,0,-1] danji_list = [] for i in range(N): for j in range(N): if arr[i][j]: arr[i][j] = 0 c = 1 q = deque() q.append([i,j]) while q: p = q.popleft() for d in range(4): nr, nc = p[0]+dr[d], p[1]+dc[d] if 0<=nr<N and 0<=nc<N: if arr[nr][nc]: q.append([nr,nc]) arr[nr][nc] = 0 c += 1 danji_list.append(c) print(len(danji_list)) for i in sorted(danji_list): print(i)

[ "woodg1207@gmail.com" ]

woodg1207@gmail.com

77ceff54bf05ef0ec310abe67194e4c272925c48

a7b66311c2ce113789933ec3162f1128b2862f13

/app/closeLoop/ForcastDiffFactor.py

08170df61a83a596a2f558df9d51de995411210f

[ "MIT" ]

permissive

ChanJeunlam/geolearn

214b2c42359ea1164b39117fad2d7470adeb6d35

791caa54eb70920823ea7d46714dc8a3e7fa7445

refs/heads/master

2023-07-16T04:13:15.526364

2021-08-16T05:24:18

null

0

null

UTF-8

Python

false

5,847

py

from hydroDL import pathSMAP, master, utils from hydroDL.master import default from hydroDL.post import plot, stat import os import matplotlib.pyplot as plt import numpy as np import torch import pandas as pd doLst = list() # doLst.append('train') doLst.append('test') doLst.append('post') saveDir = os.path.join(pathSMAP['dirResult'], 'DA') # test if 'test' in doLst: torch.cuda.set_device(2) subset = 'CONUSv2f1' tRange = [20150402, 20180401] yrStrLst = ['2015', '2016', '2017'] yfLst = list() ypLst = list() for yrStr in yrStrLst: out = os.path.join(pathSMAP['Out_L3_NA'], 'DA', 'CONUSv2f1_DA' + yrStr) df, yf, obs = master.test( out, tRange=tRange, subset=subset, batchSize=100) out = os.path.join(pathSMAP['Out_L3_NA'], 'DA', 'CONUSv2f1_LSTM' + yrStr) df, yp, obs = master.test(out, tRange=tRange, subset=subset) yf = yf.squeeze() yp = yp.squeeze() yfLst.append(yf) ypLst.append(yp) obs = obs.squeeze() # figure out how many days observation lead maskObs = 1 * ~np.isnan(obs.squeeze()) maskDay = np.zeros(maskObs.shape).astype(int) ngrid, nt = maskObs.shape for j in range(ngrid): temp = 0 for i in range(nt): maskDay[j, i] = temp if maskObs[j, i] == 1: temp = 1 else: if temp != 0: temp = temp + 1 ind = np.random.randint(0, ngrid) maskObsDay = maskObs * maskDay unique, counts = np.unique(maskObsDay, return_counts=True) maskF = (maskDay >= 1) & (maskDay <= 3) statPLst = list() statFLst = list() for k in range(3): statP = stat.statError( utils.fillNan(ypLst[k], maskF), utils.fillNan(obs, maskF)) statF = stat.statError( utils.fillNan(yfLst[k], maskF), utils.fillNan(obs, maskF)) statPLst.append(statP) statFLst.append(statF) cropFile = r'/mnt/sdb/Data/Crop/cropRate_CONUSv2f1.csv' cropRate = pd.read_csv(cropFile, dtype=np.float, header=None).values # croprate - 0 corn, 4 soybean, 22 spring wheat, 23 winter wheat dataGrid = [(statPLst[0]['RMSE'] - statFLst[0]['RMSE']) / statPLst[0]['RMSE'], (statPLst[1]['RMSE'] - statFLst[1]['RMSE']) / statPLst[1]['RMSE'], (statPLst[2]['RMSE'] - statFLst[2]['RMSE']) / statPLst[2]['RMSE'], ] prcp = df.getDataTs('APCP_FORA').squeeze() dataTs = [[obs, ypLst[0], yfLst[0]], [obs, ypLst[1], yfLst[1]], [obs, ypLst[2], yfLst[2]], [prcp]] crd = df.getGeo() t = df.getT() mapNameLst = ['dRMSE 2015', 'dRMSE 2016', 'dRMSE 2017'] tsNameLst = ['obs', 'prj', 'fore'] tBar = [utils.time.t2dt(20160401), utils.time.t2dt(20170401)] #plt.tight_layout() plot.plotTsMap( dataGrid, dataTs, lat=crd[0], lon=crd[1], t=t, mapNameLst=mapNameLst, isGrid=True, multiTS=True, linewidth=1, figsize=(10, 10), tBar=tBar) # see result for different seasons tRangeLst = [[20180101, 20180201], [20180201, 20180301], [20180301, 20180401], [20160401, 20160501], [20160501, 20160601], [20160601, 20160701], [20160701, 20160801], [20160801, 20160901], [20160901, 20161001], [20161001, 20161101], [20161101, 20161201], [20161201, 20170101], [20170101, 20170201], [20170201, 20170301], [20170301, 20170401], [20170401, 20170501], [20170501, 20170601], [20170601, 20170701], [20170701, 20170801], [20170801, 20170901], [20170901, 20171001], [20171001, 20171101], [20171101, 20171201], [20171201, 20180101]] tAllR = [20150402, 20180401] tAllA = utils.time.tRange2Array(tAllR) statPLst = list() statFLst = list() for k in range(12): tRLst = [tRangeLst[k], tRangeLst[k + 12]] temp = list() for tR in tRLst: tA = utils.time.tRange2Array(tR) ind0 = np.array(range(nt)) ind1, ind2 = utils.time.intersect(tAllA, tA) temp.append(ind1) indT = np.concatenate(temp) yfTemp = utils.fillNan(yf, maskF)[:, indT] ypTemp = utils.fillNan(yp, maskF)[:, indT] obsTemp = utils.fillNan(obs, maskF)[:, indT] statPLst.append(stat.statError(ypTemp, obsTemp)) statFLst.append(stat.statError(yfTemp, obsTemp)) import matplotlib matplotlib.rcParams.update({'font.size': 14}) matplotlib.rcParams.update({'lines.linewidth': 2}) matplotlib.rcParams.update({'lines.markersize': 6}) labCrop = ['Corn', 'Spring wheat', 'Winter wheat'] indCrop = [0, 22, 23] cropFile = r'/mnt/sdb/Data/Crop/cropRate_CONUSv2f1.csv' cropRate = pd.read_csv(cropFile, dtype=np.float, header=None).values key = 'RMSE' [lat, lon] = df.getGeo() fig, axes = plt.subplots(1, 3, figsize=[12, 5]) for k in range(3): grid, uy, ux = utils.grid.array2grid( cropRate[:, indCrop[k]], lat=lat, lon=lon) plot.plotMap( grid, ax=axes[k], lat=uy, lon=ux, title=labCrop[k] + ' percentage') plt.tight_layout() fig.show() import matplotlib matplotlib.rcParams.update({'font.size': 14}) matplotlib.rcParams.update({'lines.linewidth': 2}) matplotlib.rcParams.update({'lines.markersize': 6}) indLst = [cropRate[:, 0] > 30, cropRate[:, 22] > 5, cropRate[:, 23] > 10] labMonth = [ 'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Agu', 'Sep', 'Oct', 'Nov', 'Dec' ] labCrop = ['Corn', 'Spring wheat', 'Winter wheat'] cLst = 'rgb' dataBox = list() for iC in range(len(indLst)): dataBox = list() for k in range(12): data = statPLst[k]['RMSE'][indLst[iC]] - statFLst[k]['RMSE'][ indLst[iC]] if len(data[~np.isnan(data)]) < 20: data = [] dataBox.append(data) fig = plot.plotBoxFig( dataBox, label1=labMonth, label2=[labCrop[iC]], sharey=True, figsize=[8, 3], colorLst=cLst[iC]) plt.subplots_adjust(wspace=0, hspace=0) plt.ylim(-0.02, 0.04) fig.show()

[ "geofkwai@gmail.com" ]

geofkwai@gmail.com

0a606a1b05d67e2bbd7b110945393561282c0ba4

430db754af2a7481358df2dcd7f74919c4ecddcf

/prob_tools/tools.py

6acebfcfbb108e282202e948521f5579880f9c75

[ "MIT" ]

permissive

arruda/exercicios_probabilidade

567eb318ff137bcce155142d3a951cf6b1c40515

dca3503a0b4d982e63795b775bf30b9b95440bcd

refs/heads/master

2021-01-19T19:35:24.552403

2014-10-22T18:31:42

null

0

null

UTF-8

Python

false

500

py

#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import division import math def combinacao(n, p): """ Combinação de N, P à P """ n_fat = math.factorial(n) p_fat = math.factorial(p) n_menos_p_fat = math.factorial(n-p) return n_fat / (p_fat * n_menos_p_fat) def bernuille(): pass def distribuicao_binomial(n, p, X): """ Binomial: n = Total de elementos p = probabilidade de sucesso X = variavel aleatoria """ return

[ "felipe.arruda.pontes@gmail.com" ]

felipe.arruda.pontes@gmail.com

6060cea90a85849c7a6e237732ba3d0a8e87983d

ec0e1779383bec96de803ba893de5096c563158f

/tensorflow/python/estimator/inputs/pandas_io.py

a1e418f487c5b7da6907fa945fba0165334432cf

[]

no_license

DengZhuangSouthRd/simple_tensorflow

45d8fc7c2ef9da947f11f876aff7c1e169dc457c

83d742219c4a04c61822935487626890bc735301

refs/heads/master

2021-01-18T19:05:36.414639

2017-04-01T15:06:16

86,887,616

11

1

null

UTF-8

Python

false

4,137

py

# Copyright 2017 The TensorFlow Authors. 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. # ============================================================================== """Methods to allow pandas.DataFrame.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np from tensorflow.python.estimator.inputs.queues import feeding_functions try: # pylint: disable=g-import-not-at-top # pylint: disable=unused-import import pandas as pd HAS_PANDAS = True except IOError: # Pandas writes a temporary file during import. If it fails, don't use pandas. HAS_PANDAS = False except ImportError: HAS_PANDAS = False def pandas_input_fn(x, y=None, batch_size=128, num_epochs=1, shuffle=True, queue_capacity=1000, num_threads=1, target_column='target'): """Returns input function that would feed Pandas DataFrame into the model. Note: `y`'s index must match `x`'s index. Args: x: pandas `DataFrame` object. y: pandas `Series` object. batch_size: int, size of batches to return. num_epochs: int, number of epochs to iterate over data. If not `None`, read attempts that would exceed this value will raise `OutOfRangeError`. shuffle: bool, whether to read the records in random order. queue_capacity: int, size of the read queue. If `None`, it will be set roughly to the size of `x`. num_threads: int, number of threads used for reading and enqueueing. target_column: str, name to give the target column `y`. Returns: Function, that has signature of ()->(dict of `features`, `target`) Raises: ValueError: if `x` already contains a column with the same name as `y`, or if the indexes of `x` and `y` don't match. """ if not HAS_PANDAS: raise TypeError( 'pandas_input_fn should not be called without pandas installed') x = x.copy() if y is not None: if target_column in x: raise ValueError( 'Cannot use name %s for target column: DataFrame already has a ' 'column with that name: %s' % (target_column, x.columns)) if not np.array_equal(x.index, y.index): raise ValueError('Index for x and y are mismatched.\nIndex for x: %s\n' 'Index for y: %s\n' % (x.index, y.index)) x[target_column] = y # TODO(mdan): These are memory copies. We probably don't need 4x slack space. # The sizes below are consistent with what I've seen elsewhere. if queue_capacity is None: if shuffle: queue_capacity = 4 * len(x) else: queue_capacity = len(x) min_after_dequeue = max(queue_capacity / 4, 1) def input_fn(): """Pandas input function.""" queue = feeding_functions._enqueue_data( # pylint: disable=protected-access x, queue_capacity, shuffle=shuffle, min_after_dequeue=min_after_dequeue, num_threads=num_threads, enqueue_size=batch_size, num_epochs=num_epochs) if num_epochs is None: features = queue.dequeue_many(batch_size) else: features = queue.dequeue_up_to(batch_size) assert len(features) == len(x.columns) + 1, ('Features should have one ' 'extra element for the index.') features = features[1:] features = dict(zip(list(x.columns), features)) if y is not None: target = features.pop(target_column) return features, target return features return input_fn

[ "liuguiyangnwpu@163.com" ]

liuguiyangnwpu@163.com

b2c8ee7450114fe41b23728d52ab158c5be37155

37c38ef8ead53739b3128147da9a24c44cfccccb

/froide/helper/search.py

096eeb8474bc34da53009caf07af0861a887d59b

[ "MIT" ]

permissive

zlodej/pekel

ff102dc1c05180dfcff6a30bd944252d128e0fb5

b1114618ef032503ab49476e738e90952c4da71a

refs/heads/master

2021-05-06T15:38:28.301853

2017-12-02T11:33:19

102,724,490

0

null

UTF-8

Python

false

3,627

py

from haystack.fields import NgramField from haystack.exceptions import MissingDependency class SuggestField(NgramField): pass try: from haystack.backends.elasticsearch_backend import ( ElasticsearchSearchEngine, ElasticsearchSearchBackend, FIELD_MAPPINGS ) except (ImportError, MissingDependency): pass else: class SuggestField(NgramField): # noqa field_type = 'suggest' FIELD_MAPPINGS['suggest'] = {'type': 'string', 'analyzer': 'suggest_analyzer'} class FroideElasticsearchSearchBackend(ElasticsearchSearchBackend): # Settings to add an custom suggest analyzer DEFAULT_SETTINGS = { 'settings': { "analysis": { "analyzer": { "ngram_analyzer": { "type": "custom", "tokenizer": "standard", "filter": ["haystack_ngram", "lowercase"] }, "edgengram_analyzer": { "type": "custom", "tokenizer": "standard", "filter": ["haystack_edgengram", "lowercase"] }, "suggest_analyzer": { "filter": ["lowercase", "asciifolding"], "type": "custom", "tokenizer": "froide_autocomplete_ngram" } }, "tokenizer": { "haystack_ngram_tokenizer": { "type": "nGram", "min_gram": 3, "max_gram": 15, }, "haystack_edgengram_tokenizer": { "type": "edgeNGram", "min_gram": 2, "max_gram": 15, "side": "front" }, "froide_autocomplete_ngram": { "type": "edgeNGram", "min_gram": 1, "max_gram": 15, "token_chars": ["letter", "digit"] } }, "filter": { "haystack_ngram": { "type": "nGram", "min_gram": 3, "max_gram": 15 }, "haystack_edgengram": { "type": "edgeNGram", "min_gram": 2, "max_gram": 15 } } } } } class FroideElasticsearchSearchEngine(ElasticsearchSearchEngine): backend = FroideElasticsearchSearchBackend class SearchQuerySetWrapper(object): """ Decorates a SearchQuerySet object using a generator for efficient iteration """ def __init__(self, qs, model): self.qs = qs self.model = model def count(self): return self.qs.count() def __iter__(self): for result in self.qs: yield result.object def __getitem__(self, key): if isinstance(key, int) and (key >= 0 or key < self.count()): # return the object at the specified position return self.qs[key].object # Pass the slice/range on to the delegate return SearchQuerySetWrapper(self.qs[key], self.model)

[ "mail@stefanwehrmeyer.com" ]

mail@stefanwehrmeyer.com

a23d5a870a4d32a4c8c889089b00f6e56ee3dd50

73c2ec3edf0f6eaea4ce1f73e910f02592119a42

/mmdet/models/utils/fpn_utils.py

ab7558ff1ecd6d699cd8724dd5260b276affb28f

[ "Apache-2.0" ]

permissive

violet998/video_class_agnostic_segmentation

ab9b496415857678979a70890cb68e92fa014061

c4614fe675e8a5352012f603c15bc24fb43d690c

refs/heads/main

2023-04-20T15:31:37.699645

2021-04-22T16:41:26

null

0

null

UTF-8

Python

false

425

py

import torch import torch.nn.functional as F def merge_fpn(x, average=True): max_size = x[0].shape merged_fpn = [] for i, _ in enumerate(x): merged_fpn.append(F.interpolate(x[i], max_size[-2:])) if average: return torch.stack(merged_fpn).mean(dim=0) else: concat = torch.stack(merged_fpn) return concat.permute(1,0,2,3,4).reshape(concat.shape[1], -1, *concat.shape[-2:])

[ "mennatul@ualberta.ca" ]

mennatul@ualberta.ca

7099ddfcc80ff50780eeb6bea1817b88a9fa94f2

70d929497cbd70bb40ed939f3aa0ce56c3f7d816

/pandas/core/groupby/ops.pyi

58a34d0c2081a8e25b9bb1f4bab161d88906e3f0

[ "MIT" ]

permissive

matangover/python-type-stubs

abd4bc46f9841d0a2c44e1597055019d21f9ee70

15285c6b88dc684d9de9bfdaf8b72d4eb7c3e257

refs/heads/main

2023-07-13T04:19:03.481222

2021-08-05T20:26:18

399,435,272

0

MIT

2021-08-24T11:11:57

2021-08-24T11:11:56

null

UTF-8

Python

false

2,824

pyi

import numpy as np from pandas._typing import FrameOrSeries as FrameOrSeries from pandas.core.groupby import grouper as grouper from pandas.core.indexes.api import Index as Index from pandas.core.series import Series as Series from typing import List, Optional, Sequence, Tuple class BaseGrouper: axis = ... sort = ... group_keys = ... mutated = ... indexer = ... def __init__(self, axis: Index, groupings: Sequence[grouper.Grouping], sort: bool=..., group_keys: bool=..., mutated: bool=..., indexer: Optional[np.ndarray]=...) -> None: ... @property def groupings(self) -> List[grouper.Grouping]: ... @property def shape(self): ... def __iter__(self) : ... @property def nkeys(self) -> int: ... def get_iterator(self, data: FrameOrSeries, axis: int=...) : ... def apply(self, f, data: FrameOrSeries, axis: int=...) : ... def indices(self): ... @property def codes(self) -> List[np.ndarray]: ... @property def levels(self) -> List[Index]: ... @property def names(self): ... def size(self) -> Series: ... def groups(self): ... def is_monotonic(self) -> bool: ... def group_info(self): ... def codes_info(self) -> np.ndarray: ... def ngroups(self) -> int: ... @property def reconstructed_codes(self) -> List[np.ndarray]: ... def result_index(self) -> Index: ... def get_group_levels(self): ... def aggregate(self, values, how: str, axis: int=..., min_count: int=...) -> Tuple[np.ndarray, Optional[List[str]]]: ... def transform(self, values, how: str, axis: int=..., **kwargs) : ... def agg_series(self, obj: Series, func) : ... class BinGrouper(BaseGrouper): bins = ... binlabels = ... mutated = ... indexer = ... def __init__(self, bins, binlabels, filter_empty: bool=..., mutated: bool=..., indexer=...) -> None: ... def groups(self): ... @property def nkeys(self) -> int: ... def get_iterator(self, data: FrameOrSeries, axis: int=...) : ... def indices(self): ... def group_info(self): ... def reconstructed_codes(self) -> List[np.ndarray]: ... def result_index(self): ... @property def levels(self): ... @property def names(self): ... @property def groupings(self) -> List[grouper.Grouping]: ... def agg_series(self, obj: Series, func) : ... class DataSplitter: data = ... labels = ... ngroups = ... axis = ... def __init__(self, data: FrameOrSeries, labels, ngroups: int, axis: int=...) -> None: ... def slabels(self): ... def sort_idx(self): ... def __iter__(self) : ... class SeriesSplitter(DataSplitter): ... class FrameSplitter(DataSplitter): def fast_apply(self, f, names): ... def get_splitter(data: FrameOrSeries, *args, **kwargs) -> DataSplitter: ...

[ "gram@geekraver.com" ]

gram@geekraver.com

f3ce2b0bddb87af3a6913e654894d0f19c5a9fe7

436166fda7a671805b8fa6fc06e68bf7d42f9be6

/test/boost.py

f977bb0860e75e9f0cee74eff9cad1e18a818acf

[]

no_license

VitalyVorobyev/libLinAl

1e4872feb0e5deb70d9c3acc2e31e676e27818c2

b815efeee109922ffd28d97b9253f636403aa999

refs/heads/master

2021-01-22T08:39:29.897025

2020-08-28T04:06:52

81,914,520

0

null

UTF-8

Python

false

1,131

py

""" Boost """ import numpy as np import matplotlib.pyplot as plt from liblinal import vect, lvect def boost_test(): """ Boost unit test """ boost_list = np.linspace(0.0001, 0.9, 500) txprime = np.array([lvect(1., 0, 0, 0).boost(vect(bx, 0, 0)).as_list[:2] for bx in boost_list]) tprime, xprime = txprime[:, 0], txprime[:, 1] plt.rc('text', usetex=True) plt.rc('font', family='serif') plt.rc('font', size=22) plt.style.use('seaborn-white') label_size = 28 plt.figure(num=1, figsize=(6, 4), dpi=100) plt.plot(boost_list, tprime, 'b-', markersize=12) plt.ylabel(r'$t^{\prime}$', fontsize=label_size) plt.xlabel(r'$\beta$', fontsize=label_size) plt.tight_layout(pad=.2) plt.figure(num=2, figsize=(6, 4), dpi=100) # plt.semilogy(boost_list, xprime, 'b-', markersize=12) # plt.loglog(boost_list, xprime, 'b-', markersize=12) plt.plot(boost_list, xprime, 'b-', markersize=12) plt.ylabel(r'$x^{\prime}$', fontsize=label_size) plt.xlabel(r'$\beta$', fontsize=label_size) plt.tight_layout(pad=.2) plt.show() boost_test()

[ "vit.vorobiev@gmail.com" ]

vit.vorobiev@gmail.com