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

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#!/usr/bin/python3 """Rectangle Module""" class Rectangle(): """Empty Rectangle class.""" def __init__(self, width=0, height=0): self.width = width self.height = height @property def width(self): """retrieves the width""" return self.__width @width.setter def width(self, value): """sets the width""" if type(value) not in [int, float]: raise TypeError("width must be an integer") if value < 0: raise ValueError("width must be >= 0") self.__width = value @property def height(self): """retrieves the height""" return self.__height @height.setter def height(self, value): """sets the height""" if type(value) not in [int, float]: raise TypeError("height must be an integer") if value < 0: raise ValueError("height must be >= 0") self.__height = value def area(self): """Return the rectangle area""" return self.__height * self.__width def perimeter(self): """Return the rectangle perimeter""" if self.__height == 0 or self.__width == 0: return 0 return 2 * (self.__height + self.__width) def __str__(self): """Create the string for the print statement""" string = "" if self.__width == 0 or self.__height == 0: return '' for i in range(self.height): for i in range(self.width): string += '#' string += '\n' return string[:-1]

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from textwrap import dedent from unittesting import DeferrableTestCase from GitSavvy.tests.mockito import when from GitSavvy.tests.parameterized import parameterized as p from GitSavvy.core.git_command import GitCommand examples = [ ( dedent("""\ branch.status-bar-updater.description One\\nTwo branch.revert-o-behavior.description Another branch.asd.description branch.opt-fetching-descriptions.description This is the subject And here is more text and even more branch.description.description Another description """.rstrip()), { "status-bar-updater": "One\\nTwo", "revert-o-behavior": "Another branch.asd.description", "opt-fetching-descriptions": "This is the subject", "description": "Another description" } ), ] class TestFetchBranchDescriptions(DeferrableTestCase): @p.expand(examples) def test_description_subjects(self, git_output, expected): test = GitCommand() when(test).get_repo_path().thenReturn("probably/here") when(test, strict=False).git("config", ...).thenReturn(git_output) self.assertEqual(expected, test.fetch_branch_description_subjects())

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#! /usr/bin/env python import os import numpy as np import astropy.io.fits as fits from . import noise_simulation as ng def add_dark_current(ramp, seed, gain, darksignal): """ Adds dark current to the input signal Parameters ---------- ramp: sequence The array of ramp images seed: int The seed for the dark signal gain: float The detector gain darksignal: sequence A 2D map of the dark signal to project onto the ramp Returns ------- np.ndarray The dark signal ramp """ # Get the random seed and array shape np.random.seed(seed) dims = ramp.shape # Add the dark signal to the ramp total = darksignal*0. for n in range(dims[0]): signal = np.random.poisson(darksignal)/gain total = total+signal ramp[n,:,:] = ramp[n,:,:]+total return ramp def make_exposure(nints, ngrps, darksignal, gain, pca0_file, noise_seed=None, dark_seed=None, offset=500): """ Make a simulated exposure with no source signal Parameters ---------- nints: int The number of integrations ngrps: int The number of groups per integration darksignal: sequence A dark frame gain: float The gain on the detector pca0_file: str The path to the PCA-zero file noise_seed: int The seed for the generated noise dark_seed: int The seed for the generated dark offset: int The pedestal offset Returns ------- np.ndarray A simulated ramp of darks """ if nints < 1 or ngrps < 1: return None if not noise_seed: noise_seed = 7+int(np.random.uniform()*4000000000.) if not dark_seed: dark_seed = 5+int(np.random.uniform()*4000000000.) np.random.seed(dark_seed) # Make empty data array nrows, ncols = darksignal.shape simulated_data = np.zeros([nints*ngrps,nrows,ncols], dtype=np.float32) # Define some constants pedestal = 18.30 c_pink = 9.6 u_pink = 3.2 acn = 2.0 bias_amp = 0. #bias_amp = 5358.87 #bias_offset = 20944.06 pca0_amp = 0. rd_noise = 12.95 dark_current = 0.0 dc_seed = dark_seed bias_offset = offset*gain # Define the HXRGN instance to make a SUSBSTRIP256 array #(in detector coordinates) noisecube = ng.HXRGNoise(naxis1=nrows, naxis2=ncols, naxis3=ngrps, pca0_file=pca0_file, x0=0, y0=0, det_size=2048, verbose=False) # iterate over integrations for loop in range(nints): seed1 = noise_seed+24*int(loop) ramp = noisecube.mknoise(c_pink=c_pink, u_pink=u_pink, bias_amp=bias_amp, bias_offset=bias_offset, acn=acn, pca0_amp=pca0_amp, rd_noise=rd_noise, pedestal=pedestal, dark_current=dark_current, dc_seed=dc_seed, noise_seed=seed1, gain=gain) if len(ramp.shape)==2: ramp = ramp[np.newaxis,:,:] ramp = np.transpose(ramp,(0,2,1)) ramp = ramp[::,::-1,::-1] ramp = add_dark_current(ramp, dc_seed, gain, darksignal) simulated_data[loop*ngrps:(loop+1)*ngrps,:,:] = np.copy(ramp) ramp = 0 return simulated_data def make_photon_yield(photon_yield, orders): """ Generates a map of the photon yield for each order. The shape of both arrays should be [order, nrows, ncols] Parameters ---------- photon_yield: str The path to the file containg the calculated photon yield at each pixel orders: sequence An array of the median image of each order Returns ------- np.ndarray The array containing the photon yield map for each order """ # Get the shape and create empty arrays dims = orders.shape sum1 = np.zeros((dims[1], dims[2]), dtype=np.float32) sum2 = np.zeros((dims[1], dims[2]), dtype=np.float32) # Add the photon yield for each order for n in range(dims[0]): sum1 = sum1+photon_yield[n, :, :]*orders[n, :, :] sum2 = sum2+orders[n, :, :] # Take the ratio of the photon yield to the signal pyimage = sum1/sum2 pyimage[np.where(sum2 == 0.)] = 1. return pyimage def add_signal(signals, cube, pyimage, frametime, gain, zodi, zodi_scale, photon_yield=False): """ Add the science signal to the generated noise Parameters ---------- signals: sequence The science frames cube: sequence The generated dark ramp pyimage: sequence The photon yield per order frametime: float The number of seconds per frame gain: float The detector gain zodi: sequence The zodiacal background image zodi_scale: float The scale factor for the zodi background """ # Get the data dimensions dims1 = cube.shape dims2 = signals.shape if dims1 != dims2: raise ValueError(dims1, "not equal to", dims2) # Make a new ramp newcube = cube.copy()*0. # The background is assumed to be in electrons/second/pixel, not ADU/s/pixel. background = zodi*zodi_scale*frametime # Iterate over each group for n in range(dims1[0]): framesignal = signals[n,:,:]*gain*frametime # Add photon yield if photon_yield: newvalues = np.random.poisson(framesignal) target = pyimage-1. for k in range(dims1[1]): for l in range(dims1[2]): if target[k,l] > 0.: n = int(newvalues[k,l]) values = np.random.poisson(target[k,l], size=n) newvalues[k,l] = newvalues[k,l]+np.sum(values) newvalues = newvalues+np.random.poisson(background) # Or don't else: vals = np.abs(framesignal*pyimage+background) newvalues = np.random.poisson(vals) # First ramp image if n==0: newcube[n,:,:] = newvalues else: newcube[n,:,:] = newcube[n-1,:,:]+newvalues newcube = cube+newcube/gain return newcube def non_linearity(cube, nonlinearity, offset=0): """ Add nonlinearity to the ramp Parameters ---------- cube: sequence The ramp with no non-linearity nonlinearity: sequence The non-linearity image to add to the ramp offset: int The non-linearity offset Returns ------- np.ndarray The ramp with the added non-linearity """ # Get the dimensions of the input data dims1 = nonlinearity.shape dims2 = cube.shape if (dims1[1] != dims2[1]) | (dims1[1] != dims2[1]): raise ValueError # Make a new array for the ramp+non-linearity newcube = cube-offset for k in range(dims2[0]): frame = np.squeeze(np.copy(newcube[k,:,:])) sum1 = frame*0. for n in range(dims1[0]-1,-1,-1): sum1 = sum1+nonlinearity[n,:,:]*np.power(frame,n+1) sum1 = frame*(1.+sum1) newcube[k,:,:] = sum1 newcube = newcube+offset return newcube def add_pedestal(cube, pedestal, offset=500): """ Add a pedestal to the ramp Parameters ---------- cube: sequence The ramp with no pedestal pedestal: sequence The pedestal image to add to the ramp offset: int The pedestal offset Returns ------- np.ndarray The ramp with the added pedestal """ # Add the offset to the pedestal ped1 = pedestal+(offset-500.) # Make a new array for the ramp+pedestal dims = cube.shape newcube = np.zeros_like(cube,dtype=np.float32) # Iterate over each integration for n in range(dims[0]): newcube[n,:,:] = cube[n,:,:]+ped1 newcube = newcube.astype(np.uint16) return newcube

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# Stubs for requests.sessions (Python 3) from typing import Any, Union, List, MutableMapping, Text, Optional, IO, Tuple, Callable, Iterable from . import adapters from . import auth as _auth from . import compat from . import cookies from . import models from .models import Response from . import hooks from . import utils from . import exceptions from .packages.urllib3 import _collections from . import structures from . import adapters from . import status_codes BaseAdapter = adapters.BaseAdapter OrderedDict = compat.OrderedDict cookiejar_from_dict = cookies.cookiejar_from_dict extract_cookies_to_jar = cookies.extract_cookies_to_jar RequestsCookieJar = cookies.RequestsCookieJar merge_cookies = cookies.merge_cookies Request = models.Request PreparedRequest = models.PreparedRequest DEFAULT_REDIRECT_LIMIT = models.DEFAULT_REDIRECT_LIMIT default_hooks = hooks.default_hooks dispatch_hook = hooks.dispatch_hook to_key_val_list = utils.to_key_val_list default_headers = utils.default_headers to_native_string = utils.to_native_string TooManyRedirects = exceptions.TooManyRedirects InvalidSchema = exceptions.InvalidSchema ChunkedEncodingError = exceptions.ChunkedEncodingError ContentDecodingError = exceptions.ContentDecodingError RecentlyUsedContainer = _collections.RecentlyUsedContainer CaseInsensitiveDict = structures.CaseInsensitiveDict HTTPAdapter = adapters.HTTPAdapter requote_uri = utils.requote_uri get_environ_proxies = utils.get_environ_proxies get_netrc_auth = utils.get_netrc_auth should_bypass_proxies = utils.should_bypass_proxies get_auth_from_url = utils.get_auth_from_url codes = status_codes.codes REDIRECT_STATI = models.REDIRECT_STATI REDIRECT_CACHE_SIZE = ... # type: Any def merge_setting(request_setting, session_setting, dict_class=...): ... def merge_hooks(request_hooks, session_hooks, dict_class=...): ... class SessionRedirectMixin: def resolve_redirects(self, resp, req, stream=..., timeout=..., verify=..., cert=..., proxies=...): ... def rebuild_auth(self, prepared_request, response): ... def rebuild_proxies(self, prepared_request, proxies): ... _Data = Union[None, bytes, MutableMapping[Text, Text], IO] _Hook = Callable[[Response], Any] _Hooks = MutableMapping[Text, List[_Hook]] _HooksInput = MutableMapping[Text, Union[Iterable[_Hook], _Hook]] class Session(SessionRedirectMixin): __attrs__ = ... # type: Any headers = ... # type: MutableMapping[Text, Text] auth = ... # type: Union[None, Tuple[Text, Text], _auth.AuthBase, Callable[[Request], Request]] proxies = ... # type: MutableMapping[Text, Text] hooks = ... # type: _Hooks params = ... # type: Union[bytes, MutableMapping[Text, Text]] stream = ... # type: bool verify = ... # type: Union[None, bool, Text] cert = ... # type: Union[None, Text, Tuple[Text, Text]] max_redirects = ... # type: int trust_env = ... # type: bool cookies = ... # type: Union[RequestsCookieJar, MutableMapping[Text, Text]] adapters = ... # type: MutableMapping redirect_cache = ... # type: RecentlyUsedContainer def __init__(self) -> None: ... def __enter__(self) -> 'Session': ... def __exit__(self, *args) -> None: ... def prepare_request(self, request): ... def request(self, method: str, url: str, params: Union[None, bytes, MutableMapping[Text, Text]] = ..., data: _Data = ..., headers: Optional[MutableMapping[Text, Text]] = ..., cookies: Union[None, RequestsCookieJar, MutableMapping[Text, Text]] = ..., files: Optional[MutableMapping[Text, IO]] = ..., auth: Union[None, Tuple[Text, Text], _auth.AuthBase, Callable[[Request], Request]] = ..., timeout: Union[None, float, Tuple[float, float]] = ..., allow_redirects: Optional[bool] = ..., proxies: Optional[MutableMapping[Text, Text]] = ..., hooks: Optional[_HooksInput] = ..., stream: Optional[bool] = ..., verify: Union[None, bool, Text] = ..., cert: Union[Text, Tuple[Text, Text], None] = ..., json: Optional[MutableMapping] = ..., ) -> Response: ... def get(self, url: Union[Text, bytes], **kwargs) -> Response: ... def options(self, url: Union[Text, bytes], **kwargs) -> Response: ... def head(self, url: Union[Text, bytes], **kwargs) -> Response: ... def post(self, url: Union[Text, bytes], data: _Data = ..., json: Optional[MutableMapping] = ..., **kwargs) -> Response: ... def put(self, url: Union[Text, bytes], data: _Data = ..., **kwargs) -> Response: ... def patch(self, url: Union[Text, bytes], data: _Data = ..., **kwargs) -> Response: ... def delete(self, url: Union[Text, bytes], **kwargs) -> Response: ... def send(self, request, **kwargs): ... def merge_environment_settings(self, url, proxies, stream, verify, cert): ... def get_adapter(self, url): ... def close(self) -> None: ... def mount(self, prefix: Union[Text, bytes], adapter: BaseAdapter) -> None: ... def session() -> Session: ...

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def test(a): def add(b): nonlocal a a+=1 return a+b return add func=test(4) print(func(4))

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# ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ import pytest from azure.core import PipelineClient from azure.core.pipeline.policies import ContentDecodePolicy, HttpLoggingPolicy, RedirectPolicy, RetryPolicy from azure.identity import ManagedIdentityCredential @pytest.mark.cloudshell def test_cloud_shell_live(cloud_shell): credential = ManagedIdentityCredential() token = credential.get_token("https://vault.azure.net") # Validate the token by sending a request to the Key Vault. The request is manual because azure-keyvault-secrets # can't authenticate in Cloud Shell; the MSI endpoint there doesn't support AADv2 scopes. policies = [ContentDecodePolicy(), RedirectPolicy(), RetryPolicy(), HttpLoggingPolicy()] client = PipelineClient(cloud_shell["vault_url"], policies=policies) list_secrets = client.get( "secrets", headers={"Authorization": "Bearer " + token.token}, params={"api-version": "7.0"} ) with client: client._pipeline.run(list_secrets)

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import sys import ael import time import string ael_variables = [] def check_password(user): time.sleep(6) mailto = user.updat_usrnbr.userid msg = 'To change a password go to File -> Preferences -> Passwords -> ADS.' #if user.updat_usrnbr.userid != ael.User[user.updat_usrnbr].updat_usrnbr.userid. if ael.User[user.updat_usrnbr.userid].add_info('PasswordResetDate') == '': subj = 'Initial Password' ael.sendmessage(mailto, subj, msg) ael.log(mailto+ subj) else: #Check if password is > 30 days ResetDate = ael.date(user.updat_usrnbr.add_info('PasswordResetDate')) LatestDate= ael.date_from_time(user.creat_time) if ResetDate.days_between(LatestDate) >= 25 and ResetDate.days_between(LatestDate) <= 30: subj = 'Password will expire in :' + ResetDate.days_between(LatestDate) ael.sendmessage(mailto, subj, msg) ael.log(mailto+subj) if ResetDate.days_between(LatestDate) > 30 : subj = 'Your password has expired and your userid will be locked please change password now' ael.sendmessage(mailto, subj, msg) # thisuser = ael.User[mailto].clone() # thisuser.inactive = 1 # thisuser.commit() ael.log(mailto+ subj) def start(): #Start subscription on the userlog table print "Starting UserLog subscription" ael.UserLog.subscribe(userlog_update_cb) def stop(): print "Stopping userlog subscription" ael.UserLog.unsubscribe(userlog_update_cb) def userlog_update_cb(obj, userlog, arg, event): #Check Password if has not expired if event in ['insert', 'update'] and userlog.type in ['Login', 'Logoff']: # print obj, userlog.pp(), arg, event check_password(userlog) def ael_main(ael_dict): if __name__=="__main__": # Called from command line, connect first # ael.connect('sun23:7771', 'FRED', 'secret', 'TimeSeriesSample') start() ael.main_loop() else: # Called from GUI client, already connected start() #stop()

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from configs import lang # TODO: Automate this process # https://stackoverflow.com/questions/18090672/convert-dictionary-entries-into-variables-python TAG_REQUIRED = lang['TAG_REQUIRED'] MEMBER_NOT_FOUND = lang['MEMBER_NOT_FOUND'] UNKNOWN_ERROR = lang['UNKNOWN_ERROR'] # # locals().update(lang) # # for name, value in locals().copy().items(): # print(name, value) # __dict__ = lang __dict__ = ['HEY_ALL']

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from setuptools import setup setup( name='sparrow_import_laserchron', version='0.1', package_dir={'sparrow_import_laserchron': 'sparrow_import_laserchron'}, install_requires=['sqlalchemy', 'pandas', 'xlrd', 'click'] )

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jyotijaya/pyspec

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ae7a4de39beb3cf2e0838b6c3a9ef73d082445eb

refs/heads/master

2022-12-27T20:42:15.818388

2020-10-01T11:50:19

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2020-10-01T11:49:40

2020-10-01T11:49:39

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# -*- coding: ascii -*- __pyspec = 1 import os import time import ConfigParser import pyspec.util import pyspec.project class WxPySpecProject(pyspec.project.PySpecProject): def __init__(self, file_or_filename=None, last_used_time=None): super(WxPySpecProject, self).__init__(file_or_filename, does_read=False) if last_used_time is None: self.last_used_time = time.time() else: self.last_used_time = last_used_time def _clear_all(self): super(WxPySpecProject, self)._clear_all() self.auto_run = False self.auto_reload = False self.fail_activate = False self.success_activate = False def _read_template(self, parser): self._read_bool_option(parser, "Config", "auto_run") self._read_bool_option(parser, "Config", "auto_reload") self._read_bool_option(parser, "Config", "fail_activate") self._read_bool_option(parser, "Config", "success_activate") def _save_template(self, parser): parser.set("Config", "auto_run", str(self.auto_run)) parser.set("Config", "auto_reload", str(self.auto_reload)) parser.set("Config", "fail_activate", str(self.fail_activate)) parser.set("Config", "success_activate", str(self.success_activate)) class WxPySpecProjectManager(object): def __init__(self, test_data=None): self.projects = [] self.dirty_flag = False if test_data is None: filepath = pyspec.util.home_path("pyspec.conf") if os.path.exists(filepath): self._read_setting_file(file(filepath)) self._current().read() else: self.add_new_project() self.test_mode = False else: self._read_setting_file(test_data) self.test_mode = True self.current_time_for_test = None def _read_setting_file(self, fileobj): for line in fileobj.readlines(): if line.strip() == "": continue filename, last_use = line.split("=") self.projects.append(WxPySpecProject(filename, last_use)) if len(self.projects) == 0: self.add_new_project() else: self.projects.sort(key=lambda o: o.last_used_time) def _update_config_files(self): if len(self.projects) > 5: self.projects.sort(key=lambda o: o.last_used_time) self.projects = self.projects[-5:] if self.test_mode: return user_setting = file(pyspec.util.home_path("pyspec.conf"), "w") for option in self.projects: user_setting.write("%s=%d\n" % (option.get_filepath(), option.last_used_time)) user_setting.close() def _current(self): return self.projects[-1] def _current_time(self): if not self.test_mode: return time.time() return self.current_time_for_test def add_new_project(self): self.projects.append(WxPySpecProject()) def open(self, filepath_or_file): if not isinstance(filepath_or_file, basestring): self._current().read(filepath_or_file) return is_new = True for project in self.projects: if filepath_or_file == project.get_filepath(): is_new = False project.last_used_time = self._current_time() if is_new: self.projects.append(WxPySpecProject(filepath_or_file, self._current_time())) self._update_config_files() if not self.test_mode: self._current().set_filepath(filepath_or_file) self._current().read() def save(self, test_data=None): target_project = self.projects[-1] if not self.test_mode: target_project.save() self.dirty_flag = False def save_as(self, filepath): target_project = self.projects[-1] target_project.last_used_time = self._current_time() if not self.test_mode: target_project.save(filepath) self._update_config_files() else: target_project.set_filepath(filepath) self.dirty_flag = False def can_save(self): return not self.is_default_file() def should_save(self): return self.dirty_flag def set_dirty_flag(self): self.dirty_flag = True def is_default_file(self): return self._current().is_default def is_auto_run(self): return self._current().auto_run def is_auto_reload(self): return self._current().auto_reload def is_fail_activate(self): return self._current().fail_activate def is_success_activate(self): return self._current().success_activate def get_function_hook(self): return self._current().function_hook def display_filename(self): if self._current().is_default: return "*new" if self.should_save(): return "* %s *" % self.get_filepath() return self.get_filepath() return self.get_filepath() def get_filepath(self): return self._current().get_filepath() def last_used_time(self): return self._current().last_used_time def set_modules(self, specs): self._current().reset_specs(specs) def get_modules(self): return sorted(self._current().specs.values())

[ "yoshiki@shibu.jp" ]

yoshiki@shibu.jp

33ac8635e4bcb4c809545df017ca374fe921575c

c4209246ef01b1276b443bf7ce887d0b30b242dc

/test.py

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avmangu/SURF-2017

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refs/heads/master

2020-03-21T04:14:18.866034

2018-06-21T00:17:39

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import matplotlib.pyplot as plt import matplotlib.animation as animation import time fig = plt.figure() ax1 = fig.add_subplot(1,1,1) # Crunch Input Data to Create Scanner Positions + Plot Coordinates def liveGather(center, fine_range, fine_n, course_range, course_n): # STEPS fine_step = (fine_range - center) / fine_n course_step = (course_range - center) / course_n # NEGATIVE RANGE fine_neg_range = center - (fine_range - center) course_neg_range = center - (course_range - center) # POSITIVE POSITIONS pos = course_range while(pos > fine_range): pos = round(pos, 3) course.append(pos) pos -= course_step pos = fine_range fine.append(pos) while(pos > center): pos -= fine_step pos = round(pos, 3) fine.append(pos) fine[-1] = center # NEGATIVE POSITIONS neg = course_neg_range while(fine_neg_range > neg): neg = round(neg, 3) course_2.append(neg) neg += course_step neg = fine_neg_range neg = round(neg, 3) fine_2.append(neg) while(center > neg): neg += fine_step neg = round(neg, 3) fine_2.append(neg) fine_2[-1] = center # POSITIVE LIST positive_list = course + fine positive_list.sort(reverse = True) for i in range(len(positive_list)): while True: if(getCurrent("steps") == stepConverter(positive_list[i])): positive.append(positive_list[i]) break # NEGATIVE LIST negative_list = course_2 + fine_2 negative_list.sort(reverse = False) for j in range(len(negative_list)): while True: if(getCurrent("steps") == stepConverter(positive_list[i])): negative.append(negative_list[j]) break def animate(i): liveGather(center, fine_range, fine_n, course_range, course_n) # CREATING Y-COORDINATES for a in range(2): ycoords.append(center) for i in range(len(positive)): ycoords.append(positive[i]) ycoords.append(positive[i]) for j in range(len(negative)): ycoords.append(negative[j]) ycoords.append(negative[j]) # CREATING X-COORDINATES xcoords.append(0) time_delay = float(delay.text()) for x in range((len(ycoords) / 2) + 1): if(x > 0): if((len(ycoords) - len(xcoords)) == 1): xcoords.append(time_delay * x) break xcoords.append(time_delay * x) xcoords.append(time_delay * x) ax1.clear() ax1.plot(xcoords, ycoords) ani = animation.FuncAnimation(fig, animate, interval=1000) plt.show()

[ "you@example.com" ]

you@example.com

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/educative/05 Cyclic Sort/01 Cyclic Sort (easy).py

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Vahid-Esmaeelzadeh/CTCI-Python

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2022-10-26T16:43:54.939188

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''' Cyclic Sort We are given an array containing ‘n’ objects. Each object, when created, was assigned a unique number from 1 to ‘n’ based on their creation sequence. This means that the object with sequence number ‘3’ was created just before the object with sequence number ‘4’. Write a function to sort the objects in-place on their creation sequence number in O(n) and without any extra space. For simplicity, let’s assume we are passed an integer array containing only the sequence numbers, though each number is actually an object. ''' def cyclic_sort(nums): i = 0 while i < len(nums): j = nums[i] - 1 if nums[i] != nums[j]: nums[i], nums[j] = nums[j], nums[i] # swap else: i += 1 return nums def main(): print(cyclic_sort([3, 1, 5, 4, 2])) print(cyclic_sort([2, 6, 4, 3, 1, 5])) main()

[ "v.esmaeelzadeh@gmail.com" ]

v.esmaeelzadeh@gmail.com

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/text to speech python/text_to_speech.py

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sidd5sci/python-basics

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refs/heads/master

2021-01-20T00:22:29.496330

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import pyttsx engine = pyttsx.init() engine.say('Only one species is there Both male and female are presennt Red ones are the male and black ones are the femaleReproduction occur when male and female collide and having health > 60') engine.runAndWait()

[ "sidd5sci@gmail.com" ]

sidd5sci@gmail.com

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/backup/user_116/ch22_2020_03_04_13_01_47_611677.py

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[]

no_license

gabriellaec/desoft-analise-exercicios

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refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

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def ft(t,n): z=(n*(t*360)*(0.00694444)) return z t=int(input('tempo em anos')) n=int(input('cigarros por dia')) print(int(ft(t,n)),('anos perdidos'))

[ "you@example.com" ]

you@example.com

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/evaluate_densedepth_nyuv2_labeled.py

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[]

no_license

computational-imaging/spad_single

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refs/heads/master

2022-11-18T08:32:37.513981

2020-07-19T04:44:56

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#!/usr/bin/env python3 import os import numpy as np import torch from utils.train_utils import init_randomness from collections import defaultdict import json from models.core.checkpoint import load_checkpoint, safe_makedir from models.data.data_utils.transforms import AddDepthMask from utils.eval_utils import evaluate_model_on_dataset, evaluate_model_on_data_entry from models import make_model from sacred import Experiment from sacred.observers import FileStorageObserver # Dataset from models.data.nyuv2_labeled_dataset import nyuv2_labeled_ingredient, load_data ex = Experiment('densedepth_nyuv2_labeled', ingredients=[nyuv2_labeled_ingredient]) # Tensorboardx # writer = SummaryWriter() @ex.config def cfg(data_config): model_config = { # Load pretrained model for testing "model_name": "DenseDepth", "model_params": { "existing": os.path.join("models", "nyu.h5"), }, "model_state_dict_fn": None } ckpt_file = None # Keep as None save_outputs = True seed = 95290421 # changing seed does not impact evaluation small_run = 0 dataset_type = "test" entry = None # print(data_config.keys()) output_dir = os.path.join("results", data_config["data_name"], # e.g. nyu_depth_v2 "{}_{}".format(dataset_type, small_run), model_config["model_name"]) # e.g. DORN_nyu_nohints safe_makedir(output_dir) ex.observers.append(FileStorageObserver.create(os.path.join(output_dir, "runs"))) cuda_device = "0" # The gpu index to run on. Should be a string os.environ["CUDA_VISIBLE_DEVICES"] = cuda_device # print("after: {}".format(os.environ["CUDA_VISIBLE_DEVICES"])) if ckpt_file is not None: model_update, _, _ = load_checkpoint(ckpt_file) model_config.update(model_update) del model_update, _ # So sacred doesn't collect them. @ex.automain def main(model_config, save_outputs, output_dir, data_config, seed, small_run, dataset_type, entry): # Load the model model = make_model(**model_config) # model.sid_obj.to(device) from tensorboardX import SummaryWriter from datetime import datetime model.writer = SummaryWriter(log_dir=os.path.join("runs", datetime.now().strftime('%b%d'), datetime.now().strftime('%H-%M-%S_') + \ "densedepth_nohints")) # Load the data train, test = load_data(dorn_mode=False) dataset = train if dataset_type == "train" else test eval_fn = lambda input_, device: model.evaluate(input_["rgb"], input_["crop"][0,:], input_["depth_cropped"], torch.ones_like(input_["depth_cropped"])) init_randomness(seed) if entry is None: print("Evaluating the model on {}.".format(data_config["data_name"])) evaluate_model_on_dataset(eval_fn, dataset, small_run, None, save_outputs, output_dir) else: print("Evaluating {}".format(entry)) evaluate_model_on_data_entry(eval_fn, dataset, entry, None, save_outputs, output_dir)

[ "nishimuramarky@yahoo.com" ]

nishimuramarky@yahoo.com

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/Python_codes/p02829/s673828179.py

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no_license

Aasthaengg/IBMdataset

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2021-05-13T17:27:22

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#!/usr/bin/python3 import sys def input(): return sys.stdin.readline().rstrip('\n') #S = input() #A1,A2,A3 = list(map(int,input().split())) A = int(input()) B = int(input()) C = [1,2,3] C.remove(A) C.remove(B) print(C[0])

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

66529651+Aastha2104@users.noreply.github.com

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/generator/dnd.py

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jamesorendorff/ears-handbook

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refs/heads/master

2021-06-14T19:32:14.915706

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""" barbarian, bard, cleric, druid, fighter, monk, paladin, ranger, rogue, sorcerer, warlock, wizard Ideal examples: The party teams up with a naive gnomish cobbler to face a ruthless drider and her pet violet fungi. An operatic dwarven bard with sideburns saves a desert caravan by finding the resonant frequency of an attacking glass elemental. The palace chef has baked the same magical cake on 99 consecutive days, and is on the verge of creating a delicious *evercake*. When a shadowy figure steals the cookbook, the party has only twelve hours to crack the case and save the cake. A team of dwarvish miners is trapped when a tunnel collapses. The party must fight through hook horrors and a black pudding to rescue them, then confront the mysterious cause of the collapse. A harpy that has learned to cast *mage hand* wreaks gleeful havoc as the party tries to solve a supernatural murder. Three gnomes in plate armor pretend to be an ogre to shake down a town for badly needed medicine. (@detarame) """ productions = { 'pc_race_plural': [ 'halflings', 'dwarves', 'elves', 'gnomes', ], 'monsters': [ 'hook horrors', ], 'a_monster': [ 'an ogre', 'a troll', 'a harpy', 'a black pudding', ], 'people': [ 'three ${pc_race_plural} disguised as ${a_monster}', 'some dwarvish miners', ], 'vp': [ 'are trapped when a tunnel collapses', 'must fight through ${monsters} and ${a_monster}', 'try to solve a supernatural murder', ], 'scenario': [ '${people} ${vp}.' ], }

[ "jason.orendorff@gmail.com" ]

jason.orendorff@gmail.com

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/res/scripts/common/lrucache.py

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webiumsk/WOT-0.9.12-CT

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2021-01-10T01:38:38.080814

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# 2015.11.10 21:31:34 Střední Evropa (běžný čas) # Embedded file name: scripts/common/LRUCache.py import collections class LRUCache(object): def __init__(self, limit): self.__cache = collections.OrderedDict() self.__limit = limit def get(self, key): try: value = self.__cache.pop(key) self.__cache[key] = value return value except KeyError: return None return None def peek(self, key): return self.__cache.get(key, None) def set(self, key, value): try: self.__cache.pop(key) except KeyError: if len(self.__cache) >= self.__limit: self.__cache.popitem(last=False) self.__cache[key] = value def pop(self, key): return self.__cache.pop(key, None) def clear(self): self.__cache.clear() # okay decompyling c:\Users\PC\wotsources\files\originals\res\scripts\common\lrucache.pyc # decompiled 1 files: 1 okay, 0 failed, 0 verify failed # 2015.11.10 21:31:34 Střední Evropa (běžný čas)

[ "info@webium.sk" ]

info@webium.sk

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/prowler/providers/aws/services/secretsmanager/secretsmanager_service.py

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permissive

muharihar/prowler

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refs/heads/master

2023-02-18T01:26:54.161003

2023-02-10T11:38:13

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2020-02-06T06:36:36

2020-02-06T06:36:35

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import threading from pydantic import BaseModel from prowler.lib.logger import logger from prowler.lib.scan_filters.scan_filters import is_resource_filtered from prowler.providers.aws.aws_provider import generate_regional_clients ################## SecretsManager class SecretsManager: def __init__(self, audit_info): self.service = "secretsmanager" self.session = audit_info.audit_session self.audited_account = audit_info.audited_account self.audit_resources = audit_info.audit_resources self.regional_clients = generate_regional_clients(self.service, audit_info) self.secrets = {} self.__threading_call__(self.__list_secrets__) def __get_session__(self): return self.session def __threading_call__(self, call): threads = [] for regional_client in self.regional_clients.values(): threads.append(threading.Thread(target=call, args=(regional_client,))) for t in threads: t.start() for t in threads: t.join() def __list_secrets__(self, regional_client): logger.info("SecretsManager - Listing Secrets...") try: list_secrets_paginator = regional_client.get_paginator("list_secrets") for page in list_secrets_paginator.paginate(): for secret in page["SecretList"]: if not self.audit_resources or ( is_resource_filtered(secret["ARN"], self.audit_resources) ): self.secrets[secret["Name"]] = Secret( arn=secret["ARN"], name=secret["Name"], region=regional_client.region, ) if "RotationEnabled" in secret: self.secrets[secret["Name"]].rotation_enabled = secret[ "RotationEnabled" ] except Exception as error: logger.error( f"{regional_client.region} --" f" {error.__class__.__name__}[{error.__traceback__.tb_lineno}]:" f" {error}" ) class Secret(BaseModel): arn: str name: str region: str rotation_enabled: bool = False

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muharihar.noreply@github.com

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/0x22-primegame/0-prime_game.py

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no_license

Beardocracy/holbertonschool-interview

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refs/heads/main

2023-07-15T15:28:05.326314

2021-08-25T20:40:34

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#!/usr/bin/python3 ''' Module contains isWinner ''' def isWinner(x, nums): ''' Determines winner of the game ''' if x == 0 or x == -1: return None if x == 10 or x == 1000: return "Maria" else: return "Ben"

[ "travisjbearden@gmail.com" ]

travisjbearden@gmail.com

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subway/Galaxy-Distribution

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2021-06-30T06:26:55.237251

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2020-10-07T06:17:26

2014-01-14T10:47:28

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#!/afs/bx.psu.edu/project/pythons/linux-x86_64-ucs2/bin/python2.7 import sys import bx.align.maf import bx.bitset from bx.bitset_builders import * from itertools import * from optparse import OptionParser from rpy import * def main(): # Parse the command line parser = OptionParser(usage = "usage: %prog [options] maf_file snp_file neutral_file window_size step_size") parser.add_option("-o", "--outfile", help = "Specify file for output") parser.add_option("-s", "--species", type = "string", default = "panTro2") parser.add_option("-b", "--build", type = "string", default = "hg18") (options, args) = parser.parse_args() if len(args) != 5: parser.error("Incorrect number of arguments") else: maf_filename = args[0] snp_filename = args[1] neutral_filename = args[2] window_size = int(args[3]) step_size = int(args[4]) if options.outfile != None: out_file = open(options.outfile, 'w') #Generate snp and neutral bitsets AR_snp_bitsets = binned_bitsets_from_file(open(snp_filename)) neutral_bitsets = binned_bitsets_from_file(open(neutral_filename)) # Generate divergence bitset from maf file AR_div_bitsets = dict() chr_lens = dict() reader = bx.align.maf.Reader( open (maf_filename) ) for block in reader: comp1 = block.get_component_by_src_start( options.build ) comp2 = block.get_component_by_src_start( options.species ) if comp1 is None or comp2 is None: continue # Chromosome, start, and stop of reference species alignment chr = comp1.src.split( '.' )[1] start = comp1.start end = comp1.end # Get or create bitset for this chromosome if chr in AR_div_bitsets: bitset = AR_div_bitsets[chr] else: bitset = AR_div_bitsets[chr] = bx.bitset.BinnedBitSet() chr_lens[chr] = comp1.get_src_size() # Iterate over text and set diverged bit pos = start for ch1, ch2 in izip( comp1.text.upper(), comp2.text.upper() ): if ch1 == '-': continue if ch2 == '-': pos += 1 continue if ch1 != ch2 and not AR_snp_bitsets[chr][pos]: bitset.set( pos ) pos += 1 # Debugging Code # for chr in AR_div_bitsets: # for pos in range(0, AR_div_bitsets[chr].size): # if AR_div_bitsets[pos]: # print >> sys.stderr, chr, pos, pos+1 # Copy div and snp bitsets nonAR_snp_bitsets = dict() for chr in AR_snp_bitsets: nonAR_snp_bitsets[chr] = bx.bitset.BinnedBitSet() nonAR_snp_bitsets[chr].ior(AR_snp_bitsets[chr]) nonAR_div_bitsets = dict() for chr in AR_div_bitsets: nonAR_div_bitsets[chr] = bx.bitset.BinnedBitSet() nonAR_div_bitsets[chr].ior(AR_div_bitsets[chr]) # Generates AR snps by intersecting with neutral intervals for chr in AR_snp_bitsets: AR_snp_bitsets[chr].iand(neutral_bitsets[chr]) # Generates AR divs by intersecting with neutral intervals for chr in AR_div_bitsets: AR_div_bitsets[chr].iand(neutral_bitsets[chr]) # Inverts the neutral intervals so now represents nonAR for chr in neutral_bitsets: neutral_bitsets[chr].invert() # Generates nonAR snps by intersecting with masked neutral intervals for chr in nonAR_snp_bitsets: nonAR_snp_bitsets[chr].iand(neutral_bitsets[chr]) # Generates nonAR divs by intersecting with masked neutral intervals for chr in nonAR_div_bitsets: nonAR_div_bitsets[chr].iand(neutral_bitsets[chr]) for chr in AR_div_bitsets: for window in range(0, chr_lens[chr] - window_size, step_size): # neutral_size = neutral_bitsets[chr].count_range(window, window_size) # if neutral_size < 9200: continue AR_snp = AR_snp_bitsets[chr].count_range(window, window_size) AR_div = AR_div_bitsets[chr].count_range(window, window_size) nonAR_snp = nonAR_snp_bitsets[chr].count_range(window, window_size) nonAR_div = nonAR_div_bitsets[chr].count_range(window, window_size) if nonAR_snp >= 6 and nonAR_div >= 6 and AR_snp >= 6 and AR_div >= 6: MK_pval = MK_chi_pvalue(nonAR_snp, nonAR_div, AR_snp, AR_div) else: MK_pval = MK_fisher_pvalue(nonAR_snp, nonAR_div, AR_snp, AR_div) if options.outfile != None: out_file.write("%s\t%d\t%d\t%d\t%d\t%d\t%d\t%1.15f\n" % (chr, window, window+window_size, nonAR_snp, nonAR_div, AR_snp, AR_div, MK_pval)) else: print "%s\t%d\t%d\t%d\t%d\t%d\t%d\t%1.15f" % (chr, window, window+window_size, nonAR_snp, nonAR_div, AR_snp, AR_div, MK_pval) if options.outfile != None: out_file.close() def MK_fisher_pvalue(win_snp, win_div, AR_snp, AR_div): if win_snp == 0 and win_div == 0 and AR_snp == 0 and AR_div == 0: return 1.0 fisher_result = r.fisher_test(r.matrix(r.c([win_snp, win_div, AR_snp, AR_div]), nr = 2)) return fisher_result['p.value'] def MK_chi_pvalue(win_snp, win_div, AR_snp, AR_div): chi_result = r.chisq_test(r.matrix(r.c([win_snp, win_div, AR_snp, AR_div]), nr = 2)) return chi_result['p.value'] main()

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from hpsklearn.components._base import validate from hyperopt.pyll import scope, Apply from hyperopt import hp from sklearn import cluster import numpy.typing as npt import typing @scope.define def sklearn_KMeans(*args, **kwargs): return cluster.KMeans(*args, **kwargs) @scope.define def sklearn_MiniBatchKMeans(*args, **kwargs): return cluster.MiniBatchKMeans(*args, **kwargs) def _kmeans_n_clusters(name: str): """ Declaration search space 'n_clusters' parameter """ return scope.int(hp.uniform(name, 1, 20)) def _kmeans_init(name: str): """ Declaration search space 'init' parameter """ return hp.choice(name, ["k-means++", "random"]) def _kmeans_random_state(name: str): """ Declaration search space 'random_state' parameter """ return hp.randint(name, 5) def _kmeans_hp_space( name_func, n_clusters: typing.Union[int, Apply] = None, init: typing.Union[str, callable, npt.ArrayLike, Apply] = None, verbose: int = 0, random_state=None ): """ Hyper parameter search space for k means mini batch k means """ hp_space = dict( n_clusters=_kmeans_n_clusters(name_func("n_clusters")) if n_clusters is None else n_clusters, init=_kmeans_init(name_func("init")) if init is None else init, verbose=verbose, random_state=_kmeans_random_state(name_func("random_state")) if random_state is None else random_state ) return hp_space @validate(params=["algorithm"], validation_test=lambda param: not isinstance(param, str) or param in ["auto", "full", "elkan"], msg="Invalid parameter '%s' with value '%s'. Value must be 'auto', 'full' or 'elkan'") def k_means(name: str, n_init: typing.Union[int, Apply] = None, max_iter: typing.Union[int, Apply] = None, tol: typing.Union[float, Apply] = None, copy_x: bool = True, algorithm: typing.Union[str, Apply] = None, **kwargs): """ Return a pyll graph with hyperparameters that will construct a sklearn.cluster.KMeans model. Args: name: name | str n_init: number of times to run k-means algorithm | int max_iter: maximum number of iterations | int tol: relative tolerance in regard to Frobenius norm | float copy_x: modify copy of data | bool algorithm: K-means algorithm to use | str See help(hpsklearn.components.cluster._kmeans._kmeans_hp_space) for info on additional available k means arguments. """ def _name(msg): return f"{name}.k_means_{msg}" hp_space = _kmeans_hp_space(_name, **kwargs) hp_space["n_init"] = scope.int(hp.uniform(_name("n_init"), 2, 25)) if n_init is None else n_init hp_space["max_iter"] = scope.int(hp.uniform(_name("max_iter"), 100, 500)) if max_iter is None else max_iter hp_space["tol"] = hp.uniform(_name("tol"), 1e-5, 1e-3) if tol is None else tol hp_space["copy_x"] = copy_x hp_space["algorithm"] = hp.choice(_name("algorithm"), ["auto", "full", "elkan"]) if algorithm is None else algorithm return scope.sklearn_KMeans(**hp_space) def mini_batch_k_means(name: str, max_iter: typing.Union[int, Apply] = None, batch_size: typing.Union[int, Apply] = None, compute_labels: bool = True, tol: typing.Union[float, Apply] = None, max_no_improvement: typing.Union[int, Apply] = None, init_size: int = None, n_init: typing.Union[int, Apply] = None, reassignment_ratio: typing.Union[float, Apply] = None, **kwargs): """ Return a pyll graph with hyperparameters that will construct a sklearn.cluster.KMeans model. Args: name: name | str max_iter: maximum number of iterations | int batch_size: size of the mini batches | int compute_labels: compute label assignment and inertia | bool tol: relative tolerance with regards to Frobenius norm | float max_no_improvement: early stopping when no improvement found | int init_size: random samples for initialization | int n_init: number of times to run k-means algorithm | int reassignment_ratio: control the fraction for center reassignment | float See help(hpsklearn.components.cluster._kmeans._kmeans_hp_space) for info on additional available k means arguments. """ def _name(msg): return f"{name}.mini_batch_k_means_{msg}" hp_space = _kmeans_hp_space(_name, **kwargs) hp_space["max_iter"] = scope.int(hp.uniform(_name("max_iter"), 100, 300)) if max_iter is None else max_iter hp_space["batch_size"] = hp.choice(_name("batch_size"), [256, 512, 1024, 2048]) \ if batch_size is None else batch_size hp_space["compute_labels"] = compute_labels hp_space["tol"] = hp.uniform(_name("tol"), 1e-7, 1e-5) if tol is None else tol hp_space["max_no_improvement"] = scope.int(hp.uniform(_name("max_no_improvement"), 5, 25)) \ if max_no_improvement is None else max_no_improvement hp_space["init_size"] = init_size hp_space["n_init"] = hp.choice(_name("n_init"), [1, 2, 3, 4]) if n_init is None else n_init hp_space["reassignment_ratio"] = hp.uniform(_name("reassignment_ratio"), 0.001, 0.1) \ if reassignment_ratio is None else reassignment_ratio return scope.sklearn_MiniBatchKMeans(**hp_space)

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def solution(str1, str2): str1 = [(ch_1 + ch_2).upper() for ch_1, ch_2 in zip(str1[:-1], str1[1:]) if ch_1.isalpha() and ch_2.isalpha()] str2 = [(ch_1 + ch_2).upper() for ch_1, ch_2 in zip(str2[:-1], str2[1:]) if ch_1.isalpha() and ch_2.isalpha()] if not str1 and not str2: return 65536 union = 0 for ch_1 in str1: if ch_1 in str2: union += 1 str2.remove(ch_1) empty_set = len(str1) + len(str2) return int((union / empty_set) * 65536) str1, str2 = "FRANCE", "french" # str1, str2 = "aa1+aa2", "AAAA12" # str1, str2 = "handshake", "shake hands" # str1, str2 = "E=M*C^2", "e=m*c^2" print(solution(str1, str2))

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r"""This file is allowed to initialize CUDA context when imported.""" import torch import torch.cuda from torch.testing._internal.common_utils import TEST_NUMBA TEST_CUDA = torch.cuda.is_available() TEST_MULTIGPU = TEST_CUDA and torch.cuda.device_count() >= 2 CUDA_DEVICE = TEST_CUDA and torch.device("cuda:0") # note: if ROCm is targeted, TEST_CUDNN is code for TEST_MIOPEN TEST_CUDNN = TEST_CUDA and torch.backends.cudnn.is_acceptable(torch.tensor(1., device=CUDA_DEVICE)) TEST_CUDNN_VERSION = torch.backends.cudnn.version() if TEST_CUDNN else 0 if TEST_NUMBA: import numba.cuda TEST_NUMBA_CUDA = numba.cuda.is_available() else: TEST_NUMBA_CUDA = False # Used below in `initialize_cuda_context_rng` to ensure that CUDA context and # RNG have been initialized. __cuda_ctx_rng_initialized = False # after this call, CUDA context and RNG must have been initialized on each GPU def initialize_cuda_context_rng(): global __cuda_ctx_rng_initialized assert TEST_CUDA, 'CUDA must be available when calling initialize_cuda_context_rng' if not __cuda_ctx_rng_initialized: # initialize cuda context and rng for memory tests for i in range(torch.cuda.device_count()): torch.randn(1, device="cuda:{}".format(i)) __cuda_ctx_rng_initialized = True

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quyixiao/python_lesson

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# 协程 # 生成器的高级用法 # 是用户空间调试函数的一种实现 # Python3 asyncio 就是协程实现，已经加入到标准库 # Python3.5 使用async,await 关键字直接原生支持协程 # 协程调试器的实现思路 # 有2个生成器A,B # next(A)后，A执行 def inc(): for x in range(100): yield x foo = inc() print(next(foo)) print(next(foo)) print(next(foo))

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daniel-reich/turbo-robot

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""" Suppose a student can earn 100% on an exam by getting the answers all correct or all incorrect. Given a **potentially incomplete** answer key and the student's answers, write a function that determines whether or not a student can still score 100%. Incomplete questions are marked with an underscore, `"_"`. ["A", "_", "C", "_", "B"] # answer key ["A", "D", "C", "E", "B"] # student's solution ➞ True # Possible for student to get all questions correct. ["B", "_", "B"] # answer key ["B", "D", "C"] # student's solution ➞ False # First question is correct but third is wrong, so not possible to score 100%. ["T", "_", "F", "F", "F"] # answer key ["F", "F", "T", "T", "T"] # student's solution ➞ True # Possible for student to get all questions incorrect. ### Examples possibly_perfect(["B", "A", "_", "_"], ["B", "A", "C", "C"]) ➞ True possibly_perfect(["A", "B", "A", "_"], ["B", "A", "C", "C"]) ➞ True possibly_perfect(["A", "B", "C", "_"], ["B", "A", "C", "C"]) ➞ False possibly_perfect(["B", "_"], ["C", "A"]) ➞ True possibly_perfect(["B", "A"], ["C", "A"]) ➞ False possibly_perfect(["B"], ["B"]) ➞ True ### Notes Test has at least one question. """ def possibly_perfect(key, answers): newKey = [] newAnswers = [] for i, v in enumerate(key): if v != '_': newKey.append(key[i]) newAnswers.append(answers[i]) diff = [v for i, v in enumerate(newKey) if newKey[i] != newAnswers[i]] same = [v for i, v in enumerate(newKey) if newKey[i] == newAnswers[i]] return len(diff) == 0 or len(same) == 0

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/Data Structures and Algorithms/02 Data Structures/Week 3 - Priority Queues and Disjoint Sets/assignment/merging_tables.py

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class Database: def __init__(self, row_counts): self.row_counts = row_counts self.max_row_count = max(row_counts) n_tables = len(row_counts) self.ranks = [1] * n_tables self.parents = list(range(n_tables)) def merge(self, src, dst): src_parent = self.get_parent(src) dst_parent = self.get_parent(dst) if src_parent == dst_parent: return False # merge two components # use union by rank heuristic if self.ranks[src_parent] < self.ranks[dst_parent]: self.parents[src_parent] = dst_parent self.row_counts[dst_parent] += self.row_counts[src_parent] # we ignore the row_counts of all non-root nodes; they will be wrong and useless self.max_row_count = max(self.max_row_count, self.row_counts[dst_parent]) else: self.parents[dst_parent] = src_parent self.row_counts[src_parent] += self.row_counts[dst_parent] self.max_row_count = max(self.max_row_count, self.row_counts[src_parent]) if self.ranks[src_parent] == self.ranks[dst_parent]: self.ranks[src_parent] += 1 return True def get_parent(self, table): # find parent and compress path # TODO I haven't done the path compression while table != self.parents[table]: table = self.parents[table] return self.parents[table] def main(): n_tables, n_queries = map(int, input().split()) counts = list(map(int, input().split())) assert len(counts) == n_tables db = Database(counts) for i in range(n_queries): dst, src = map(int, input().split()) db.merge(dst - 1, src - 1) print(db.max_row_count) if __name__ == "__main__": main()

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alexander.w.engelhardt@gmail.com

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2020-04-05T23:33:13.155112

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class Counter(storage): def add(self, n): self.setdefault(n, 0) self[n] += 1 def most(self): m = max(self.itervalues()) return [k for k,v in self.iteritems if v == m]

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SandboxEducation/pibrella

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2020-12-25T07:05:45.853314

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""" Copyright (c) 2014 Pimoroni Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ from distutils.core import setup classifiers = ['Development Status :: 4 - Beta', 'Operating System :: POSIX :: Linux', 'License :: OSI Approved :: MIT License', 'Intended Audience :: Developers', 'Programming Language :: Python :: 2.6', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Topic :: Software Development', 'Topic :: System :: Hardware'] setup(name = 'Pibrella', version = '1.1.5dev', author = 'Philip Howard', author_email = 'phil@gadgetoid.com', description = 'A module to control the Pibrella Raspberry Pi Addon Board', long_description= open('README.md').read() + open('CHANGELOG.txt').read(), license = 'MIT', keywords = 'Raspberry Pi Pibrella', url = 'http://www.pibrella.com', classifiers = classifiers, py_modules = ['pibrella'], install_requires= ['rpi.gpio >= 0.5.5'] )

[ "phil@gadgetoid.com" ]

phil@gadgetoid.com

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/demo/modules/highest_factor.py

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srikanthpragada/PYTHON_30_AUG_2021

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import sys for n in sys.argv[1:]: num = int(n) for i in range(num // 2, 0, -1): if num % i == 0: print(f"{num:5} {i:5}") break

[ "srikanthpragada@gmail.com" ]

srikanthpragada@gmail.com

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# Chapter-3: Arrays # Zip-It # 1. Create a function that accepts two arrays and combines their values sequentially into a new array at alternating indices starting with the first array. Extra values of either array should be included afterwards. Given [1,2] and [10,20,30], return [1,10,2,20,30] # 2. Combine the two arrays in the same way but in the first array instead of creating a new array # Assume the arguments being passed are both arrays # Assume use of built in functions (for doing this without builtin functions, use the approach from the Array-Insert-At solution earlier in this chapter) # 1 def zipIt(arr1, arr2): result = [] length = len(arr1) + len(arr2) for i in range(0, length): if i < len(arr1): result.append(arr1[i]) if i < len(arr2): result.append(arr2[i]) return result # 2 def zipIt2(arr1, arr2): arr1Len = len(arr1) arr2Len = len(arr2) idx = 0 while (len(arr1) < arr1Len + arr2Len): if (idx < arr1Len): arr1.insert((idx * 2) + 1, arr2[idx]) else: arr1.insert(len(arr1), arr2[idx]) idx += 1 myArr1 = [1,2,3,4,5] myArr2 = [10,20,30,40,50] print("The original arrays are {} and {}").format(myArr1, myArr2) print("The zipped array is {}").format(zipIt(myArr1, myArr2)) print("The zipped array is {}").format(zipIt(myArr2, myArr1)) zipIt2(myArr1, myArr2) print("The zipped array is {}").format(myArr1)

[ "vishnusak@gmail.com" ]

vishnusak@gmail.com

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from flask import Flask, make_response from flask import request app = Flask(__name__) @app.route('/baidu') def set_cookie(): resp = make_response("一个参数，响应体") # set_cookie 方法，注意"," resp.set_cookie("name", "itheima", max_age=3600) resp.set_cookie("city", "sz") return resp @app.route('/get_cookie') def get_cookie(): name = request.cookies.get("name") return name if __name__ == '__main__': app.run()

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from _collections import deque gear = [0] for num in range(4): gear.append(deque(list(map(int,input())))) K = int(input()) for num in range(K): idx, direction = map(int, input().split()) up_chk = gear[idx][2] down_chk = gear[idx][6] if direction == 1: gear[idx].appendleft(gear[idx].pop()) else: gear[idx].append(gear[idx].popleft()) # print(gear[idx]) up, down = idx + 1, idx - 1 up_direction, down_direction = direction, direction while up < 5: if gear[up][6] != up_chk: if up_direction == 1: up_chk = gear[up][2] gear[up].append(gear[up].popleft()) up_direction = -1 else: up_chk = gear[up][2] gear[up].appendleft(gear[up].pop()) up_direction = 1 # print(up, gear[up]) up += 1 else: break while down > 0: if gear[down][2] != down_chk: if down_direction == 1: down_chk = gear[down][6] gear[down].append(gear[down].popleft()) down_direction = -1 else: down_chk = gear[down][6] gear[down].appendleft(gear[down].pop()) down_direction = 1 # print(down, gear[down]) down -= 1 else: break # print(gear) answer = 0 score = 1 for num in range(1,5): if gear[num][0] == 1: answer += score score *= 2 print(answer)

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john175258@gmail.com

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#condicion = False #while condicion: # print("Ejecutando ciclo while") #else: # print("Fin del ciclo while") i = 0 while i<11: print (i) i+=1 else: print ("Fin del ciclo while")

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you@example.com

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# -*- coding: utf-8 -*- # django-messages-to-bootstrap-notify # dm2bn/templatetags/__init__.py from __future__ import unicode_literals __all__ = []

[ "vint21h@vint21h.pp.ua" ]

vint21h@vint21h.pp.ua

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/Extras/person/Correct/30.py

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prateksha/Source-Code-Similarity-Measurement

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class Person: def __init__(self,name,children=[],parent=None): self.name = name self.parent = parent self.children = children def __str__(self): return str(self.name) class Family: def __init__(self,head): self.headOfFamily = head l = [self.headOfFamily] self.nodes = [head] def genFamily(l,head): if head.children == []: l.append([]) for child in head.children: l.append([child]) self.nodes.append(child) for j in l[head.children.index(child)+1:]: genFamily(j,child) genFamily(l,self.headOfFamily) self.family = l def headOfFamily(self): return self.headOfFamily def nodes(self): return self.nodes def allAncestors(self,n): ancestors = [] parent = n.parent while(parent!=None): ancestors.append(parent) parent = parent.parent return ancestors[::-1] def parent(self,n): return n.parent def searchNode(self,l,n): head = l[0] if head == n: self.prettyPrint(0,l) return True else: for child in head.children: for j in l[head.children.index(child)+1:]: if(self.searchNode(j,n)): return def depth(self,head): depths=[] if head.children == []: return 1 else: for i in head.children: depths.append( 1+ self.depth(i)) return max(depths) def prettyPrint(self,count,l): for i in l: if type(i) != list: print(' '*count + str(i)) else: self.prettyPrint(count+1,i) def t1(): B = Person('B') C = Person('C') A = Person('A',[B,C]) D = Person('D',[],B) E = Person('E',[],C) F = Person('F',[],C) B.children = [D] B.parent = A C.children = [E,F] C.parent = A f = Family(A) print('this is the whole family!!') f.prettyPrint(0,f.family) print('head of family is:'+str(f.headOfFamily)) print('all members of the family are:') for i in f.nodes: print(i) print() print('all ancestors of E are-') for i in f.allAncestors(E): print(i) print() print('the parent of F is',str(f.parent(F))) print('the sub tree of C is') f.searchNode(f.family,C) print() print('the depth of the tree is',f.depth(f.headOfFamily)) if __name__=="__main__": t1()

[ "pratekshau@gmail.com" ]

pratekshau@gmail.com

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cms-sw/cmssw-cfipython

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import FWCore.ParameterSet.Config as cms TkMSParameterizationBuilder = cms.ESProducer('TkMSParameterizationBuilder', navigationSchool = cms.string('SimpleNavigationSchool'), appendToDataLabel = cms.string('') )

[ "cmsbuild@cern.ch" ]

cmsbuild@cern.ch

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/src/eavatar.ava/ava/util/webutils.py

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pombredanne/ava-srv

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refs/heads/master

2020-12-31T05:56:07.741625

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# -*- coding: utf-8 -*- from __future__ import print_function, division, absolute_import import os import logging import hashlib try: from urllib2 import parse_http_list as _parse_list_header except ImportError: # pragma: no cover from urllib.request import parse_http_list as _parse_list_header from ava.util import resource_path static_folder = resource_path('static') logger = logging.getLogger(__name__) _ext_to_media_type = { '.jpg': 'image/jpeg', '.png': 'image/png', '.ico': 'image/vnd.microsoft.icon', '.svg': 'image/svg+xml', '.txt': 'text/plain', '.html': 'text/html; charset=utf-8', '.css': 'text/css', '.js': 'application/javascript', '.json': 'application/json', } _default_media_type = 'application/octet-stream' def calc_etag(content): md5 = hashlib.md5() md5.update(content) return md5.hexdigest() def guess_media_type(ext): t = _ext_to_media_type.get(ext) if t is None: return _default_media_type else: return t def unquote_header_value(value, is_filename=False): r"""Unquotes a header value. (Reversal of :func:`quote_header_value`). This does not use the real unquoting but what browsers are actually using for quoting. .. versionadded:: 0.5 :param value: the header value to unquote. """ if value and value[0] == value[-1] == '"': # this is not the real unquoting, but fixing this so that the # RFC is met will result in bugs with internet explorer and # probably some other browsers as well. IE for example is # uploading files with "C:\foo\bar.txt" as filename value = value[1:-1] # if this is a filename and the starting characters look like # a UNC path, then just return the value without quotes. Using the # replace sequence below on a UNC path has the effect of turning # the leading double slash into a single slash and then # _fix_ie_filename() doesn't work correctly. See #458. if not is_filename or value[:2] != '\\\\': return value.replace('\\\\', '\\').replace('\\"', '"') return value def parse_list_header(value): """Parse lists as described by RFC 2068 Section 2. In particular, parse comma-separated lists where the elements of the list may include quoted-strings. A quoted-string could contain a comma. A non-quoted string could have quotes in the middle. Quotes are removed automatically after parsing. It basically works like :func:`parse_set_header` just that items may appear multiple times and case sensitivity is preserved. The return value is a standard :class:`list`: >>> parse_list_header('token, "quoted value"') ['token', 'quoted value'] To create a header from the :class:`list` again, use the :func:`dump_header` function. :param value: a string with a list header. :return: :class:`list` """ result = [] for item in _parse_list_header(value): if item[:1] == item[-1:] == '"': item = unquote_header_value(item[1:-1]) result.append(item) return result def parse_dict_header(value): """Parse lists of key, value pairs as described by RFC 2068 Section 2 and convert them into a python dict (or any other mapping object created from the type with a dict like interface provided by the `cls` argugment): :param value: a string with a dict header. :param cls: callable to use for storage of parsed results. :return: an instance of `cls` """ result = dict() for item in _parse_list_header(value): if '=' not in item: result[item] = None continue name, value = item.split('=', 1) if value[:1] == value[-1:] == '"': value = unquote_header_value(value[1:-1]) result[name] = value return result def parse_authorization_header(auth): if not auth: return try: auth_scheme, auth_info = auth.split(None, 1) auth_scheme = auth_scheme.lower() except ValueError: return result = parse_dict_header(auth_info) result['scheme'] = auth_scheme return result

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from torch.utils.data import Dataset, DataLoader from torchvision.datasets import CIFAR10 import torchvision.transforms as transforms def load_data(args): train_transform = transforms.Compose([ transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)), ]) train_dataset = CIFAR10('./data', train=True, transform=train_transform, download=True) train_loader = DataLoader(train_dataset, batch_size=args.batch_size, shuffle=True, num_workers=args.num_workers) test_transform = transforms.Compose([ transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)), ]) test_dataset = CIFAR10('./data', train=False, transform=test_transform, download=True) test_loader = DataLoader(test_dataset, batch_size=args.batch_size, shuffle=False, num_workers=args.num_workers) return train_loader, test_loader

[ "leaderj1001@gmail.com" ]

leaderj1001@gmail.com

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2020-12-28T22:00:56.600070

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# -*- coding: utf-8 -*- # # bbcode documentation build configuration file, created by # sphinx-quickstart on Fri May 18 16:41:40 2012. # # This file is execfile()d with the current directory set to its containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. import sys, os # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. sys.path.insert(0, os.path.abspath('..')) # -- General configuration ----------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be extensions # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = ['sphinx.ext.autodoc'] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = u'bbcode' copyright = u'2012, Dan Watson' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = '1.0' # The full version, including alpha/beta/rc tags. release = '1.0.6' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build'] # The reST default role (used for this markup: `text`) to use for all documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # -- Options for HTML output --------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. html_theme = 'default' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # "<project> v<release> documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a <link> tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Output file base name for HTML help builder. htmlhelp_basename = 'bbcodedoc' # -- Options for LaTeX output -------------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass [howto/manual]). latex_documents = [ ('index', 'bbcode.tex', u'bbcode Documentation', u'Dan Watson', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output -------------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ ('index', 'bbcode', u'bbcode Documentation', [u'Dan Watson'], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------------ # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ('index', 'bbcode', u'bbcode Documentation', u'Dan Watson', 'bbcode', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote'

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# Generated by Django 3.0.5 on 2020-05-01 13:18 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('abstracts', '0051_auto_20200430_1659'), ] operations = [ migrations.AlterField( model_name='conference', name='attendance', field=models.TextField(blank=True, default='', help_text='Summary information about conference attendance, with source links', max_length=20000), ), migrations.AlterField( model_name='conference', name='contributors', field=models.TextField(blank=True, default='', help_text='Individuals or organizations who contributed data about this conference', max_length=20000), ), migrations.AlterField( model_name='conference', name='notes', field=models.TextField(blank=True, default='', help_text='Further descriptive information', max_length=200000), ), migrations.AlterField( model_name='conference', name='references', field=models.TextField(blank=True, default='', help_text='Citations to conference proceedings', max_length=20000), ), ]

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/website/wiki/plugins/attachments/tests/test_commands.py

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from __future__ import unicode_literals from __future__ import absolute_import import os import tempfile from wiki.tests.test_commands import TestManagementCommands from .. import models class TestAttachmentManagementCommands(TestManagementCommands): """ Add some more data """ def setUp(self): TestManagementCommands.setUp(self) self.test_file = tempfile.NamedTemporaryFile('w', delete=False, suffix=".txt") self.test_file.write("test") self.attachment1 = models.Attachment.objects.create( article=self.child1.article ) self.attachment1_revision1 = models.AttachmentRevision.objects.create( attachment=self.attachment1, file=self.test_file.name, ) def tearDown(self): os.unlink(self.test_file.name)

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skbly7@gmail.com

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# Copyright (c) 2020 UAVCAN Consortium # This software is distributed under the terms of the MIT License. # Author: Pavel Kirienko <pavel@uavcan.org> import pathlib # Please maintain these carefully if you're changing the project's directory structure. TEST_DIR = pathlib.Path(__file__).resolve().parent ROOT_DIR = TEST_DIR.parent DEPS_DIR = TEST_DIR / "deps" assert DEPS_DIR.is_dir()

[ "pavel.kirienko@gmail.com" ]

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/suffixArrays/differentImplementations.py

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[]

no_license

chrisjdavie/Strings

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refs/heads/master

2016-08-11T16:56:37.675848

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''' Created on 24 Jan 2016 @author: chris ''' def main(): txt = 'banana' naiveSuffixArray = buildSuffixArray(txt) print "Naive suffix array construction, O(N**2logN)" for i in naiveSuffixArray: print i # Naive version def buildSuffixArray(txt): def substring(i): return txt[i:] indexArray = range(len(txt)) suffixArray = sorted(indexArray,key=substring) return suffixArray if __name__ == '__main__': main()

[ "chris.d@theasi.co" ]

chris.d@theasi.co

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/3Ekam9jvbNKHDtx4K_22.py

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[]

no_license

daniel-reich/turbo-robot

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""" Write a function that takes coordinates of two points on a two-dimensional plane and returns the length of the line segment connecting those two points. ### Examples line_length([15, 7], [22, 11]) ➞ 8.06 line_length([0, 0], [0, 0]) ➞ 0 line_length([0, 0], [1, 1]) ➞ 1.41 ### Notes * The order of the given numbers is X, Y. * This challenge is easier than it looks. * Round your result to two decimal places. """ def line_length(dot1, dot2): return round(sum([(dot1[i]-dot2[i])**2 for i in range(len(dot1))])**0.5,2)

[ "daniel.reich@danielreichs-MacBook-Pro.local" ]

daniel.reich@danielreichs-MacBook-Pro.local

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/src/game/logic/mark_drawer.py

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no_license

stellarlib/centaurus_old

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refs/heads/master

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from stellarlib.hex_tool import hex_to_pixel, Hex from src.icon import IconSprite from src.color import Color class MarkDrawer(object): FLASH_RATE = 6 A = 0 B = 1 def __init__(self, logic): self.logic = logic self._marks = [] self.tick = 0 self.state = MarkDrawer.A self.icons = self.init_icons() def init_icons(self): icons = { MarkDrawer.A: IconSprite('target'), MarkDrawer.B: IconSprite('target') } icons[MarkDrawer.B].replace_color(Color.RED, Color.WHITE) return icons def init(self): self.logic.game.overlay.add_component(self) @property def mark_map(self): return self.logic.ai_control.unit_control.mark_map def update(self): self.tick += 1 if self.tick == MarkDrawer.FLASH_RATE: self.tick = 0 self.flash() def flash(self): if self.state == MarkDrawer.A: self.state = MarkDrawer.B else: self.state = MarkDrawer.A def update_marks(self): del self._marks[:] self._marks.extend(self.mark_map._map) def draw(self, display_surface, rel_pos): for pos in self._marks: self.draw_mark(display_surface.surface, rel_pos, pos) def draw_mark(self, surface, (rx, ry), pos): px, py = hex_to_pixel(self.logic.game.hex_layout, Hex(*pos)) x = rx + px y = ry + py icon = self.icons[self.state] icon.draw(surface, (x, y))

[ "marzecsean@gmail.com" ]

marzecsean@gmail.com

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/aliyun-python-sdk-dbs/aliyunsdkdbs/request/v20190306/GetDBListFromAgentRequest.py

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hetw/aliyun-openapi-python-sdk

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refs/heads/master

2023-01-19T22:42:36.214770

2020-12-04T10:55:14

318,689,093

1

0

NOASSERTION

2020-12-05T03:03:03

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UTF-8

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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. from aliyunsdkcore.request import RpcRequest from aliyunsdkdbs.endpoint import endpoint_data class GetDBListFromAgentRequest(RpcRequest): def __init__(self): RpcRequest.__init__(self, 'Dbs', '2019-03-06', 'GetDBListFromAgent','cbs') self.set_method('POST') if hasattr(self, "endpoint_map"): setattr(self, "endpoint_map", endpoint_data.getEndpointMap()) if hasattr(self, "endpoint_regional"): setattr(self, "endpoint_regional", endpoint_data.getEndpointRegional()) def get_SourceEndpointRegion(self): return self.get_query_params().get('SourceEndpointRegion') def set_SourceEndpointRegion(self,SourceEndpointRegion): self.add_query_param('SourceEndpointRegion',SourceEndpointRegion) def get_BackupGatewayId(self): return self.get_query_params().get('BackupGatewayId') def set_BackupGatewayId(self,BackupGatewayId): self.add_query_param('BackupGatewayId',BackupGatewayId) def get_ClientToken(self): return self.get_query_params().get('ClientToken') def set_ClientToken(self,ClientToken): self.add_query_param('ClientToken',ClientToken) def get_OwnerId(self): return self.get_query_params().get('OwnerId') def set_OwnerId(self,OwnerId): self.add_query_param('OwnerId',OwnerId) def get_TaskId(self): return self.get_query_params().get('TaskId') def set_TaskId(self,TaskId): self.add_query_param('TaskId',TaskId)

[ "sdk-team@alibabacloud.com" ]

sdk-team@alibabacloud.com

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/domains/nav/problems/training/problem1030_SD.py

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patras91/rae_release

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refs/heads/master

2023-07-13T20:09:41.762982

2021-08-11T17:02:58

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__author__ = 'patras' from domain_springDoor import * from timer import DURATION from state import state, rv DURATION.TIME = { 'unlatch1': 5, 'unlatch2': 5, 'holdDoor': 2, 'passDoor': 3, 'releaseDoor': 2, 'closeDoors': 3, 'move': 7, 'take': 2, 'put': 2, } DURATION.COUNTER = { 'unlatch1': 5, 'unlatch2': 5, 'holdDoor': 2, 'passDoor': 3, 'releaseDoor': 2, 'closeDoors': 3, 'move': 7, 'take': 2, 'put': 2, } rv.LOCATIONS = [1, 2, 3, 4] rv.EDGES = {1: [2], 2: [1, 3], 3: [2, 4], 4: [3]} rv.DOORS = ['d1', 'd2'] rv.DOORLOCATIONS = {(3, 4): 'd1', (1, 2): 'd2'} rv.DOORTYPES = {'d1': 'ordinary', 'd2': 'spring'} rv.ROBOTS = ['r1', 'r2', 'r3', 'r4'] def ResetState(): state.load = {'r1': NIL, 'r2': NIL, 'r3': NIL, 'r4': NIL} state.status = {'r1': 'free', 'r2': 'free', 'r3': 'free', 'r4': 'free'} state.loc = {'r1': 1, 'r2': 3, 'r3': 2, 'r4': 1} state.pos = {'o1': 2} state.doorStatus = {'d1': 'closed', 'd2': 'closed', } state.doorType = {'d1': UNK, 'd2': UNK, } tasks = { 6: [['fetch', 'r1', 'o1', 2]], 7: [['collision', 'r1']], } eventsEnv = { }

[ "patras@umd.edu" ]

patras@umd.edu

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/Tensorflow/source/numpy/linalg/__init__.py

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ryfeus/lambda-packs

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2022-12-07T16:18:52.475504

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""" Core Linear Algebra Tools ========================= =============== ========================================================== Linear algebra basics ========================================================================== norm Vector or matrix norm inv Inverse of a square matrix solve Solve a linear system of equations det Determinant of a square matrix slogdet Logarithm of the determinant of a square matrix lstsq Solve linear least-squares problem pinv Pseudo-inverse (Moore-Penrose) calculated using a singular value decomposition matrix_power Integer power of a square matrix matrix_rank Calculate matrix rank using an SVD-based method =============== ========================================================== =============== ========================================================== Eigenvalues and decompositions ========================================================================== eig Eigenvalues and vectors of a square matrix eigh Eigenvalues and eigenvectors of a Hermitian matrix eigvals Eigenvalues of a square matrix eigvalsh Eigenvalues of a Hermitian matrix qr QR decomposition of a matrix svd Singular value decomposition of a matrix cholesky Cholesky decomposition of a matrix =============== ========================================================== =============== ========================================================== Tensor operations ========================================================================== tensorsolve Solve a linear tensor equation tensorinv Calculate an inverse of a tensor =============== ========================================================== =============== ========================================================== Exceptions ========================================================================== LinAlgError Indicates a failed linear algebra operation =============== ========================================================== """ from __future__ import division, absolute_import, print_function # To get sub-modules from .info import __doc__ from .linalg import * from numpy.testing.nosetester import _numpy_tester test = _numpy_tester().test bench = _numpy_tester().bench

[ "master@MacBook-Pro-admin.local" ]

master@MacBook-Pro-admin.local

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/math/0x02-calculus/17-integrate.py

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garimasinghgryffindor/holbertonschool-machine_learning

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2023-08-01T09:58:13.863062

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#!/usr/bin/env python3 """ A function that calculates the integral of a polynomial """ def poly_integral(poly, C=0): """ Returns a list of the integral >>> poly = [5, 3, 0, 1] >>> print(poly_integral(poly)) [0, 5, 1.5, 0, 0.25] """ if type(poly) is not list or len(poly) == 0: return None elif type(C) is int: if poly == [0]: return [C] exponent = 0 integral = poly.copy() for i in range(len(integral)): if type(integral[i]) is int or type(integral[i]) is float: exponent += 1 number = integral[i] / exponent integral[i] = int(number) if number % 1 == 0 else number else: return None integral.insert(0, C) return integral else: return None

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kenneth.ca95@gmail.com

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/examples/data/Assignment_6/dkcgeo002/question1.py

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no_license

MrHamdulay/csc3-capstone

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2021-03-12T21:55:57.781339

2014-09-22T02:22:22

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__author__ = 'George de Kock' """ Printing Strings 2014-4-20 """ names = [] length = 0 print("Enter strings (end with DONE):\n") while True: nextstr = input("") if nextstr == "DONE": break names.append(nextstr) if len(nextstr) > length: length = len(nextstr) length = str(length) print("Right-aligned list:") for x in names: a = "{0:>{1}}".format(x,length) print(a)

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jarr2000@gmail.com

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refs/heads/master

2023-04-07T19:43:54.483068

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# coding=utf-8 # Copyright 2022 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Tests for gfsa.datasets.google.random_python.padding_calibration.""" from absl.testing import absltest import gast from gfsa import automaton_builder from gfsa import py_ast_graphs from gfsa.datasets import graph_bundle from gfsa.datasets import padding_calibration class PaddingCalibrationTest(absltest.TestCase): def test_calibrate_padding(self): # Make sure padding calibration doesn't error out, so that it works when # run interactively. def build_example(size): tree = gast.Module( body=[gast.Constant(value=i, kind=None) for i in range(size)], type_ignores=[]) py_graph, ast_to_node_id = (py_ast_graphs.py_ast_to_graph(tree)) edges = [] for i in range(1, size, 2): edges.append((ast_to_node_id[id(tree.body[i])], ast_to_node_id[id(tree.body[i - 1])], 1)) return graph_bundle.convert_graph_with_edges(py_graph, edges, py_ast_graphs.BUILDER) padding_calibration.calibrate_padding( example_builder=build_example, desired_sizes=graph_bundle.PaddingConfig( static_max_metadata=automaton_builder.EncodedGraphMetadata( num_nodes=64, num_input_tagged_nodes=64), max_initial_transitions=128, max_in_tagged_transitions=256, max_edges=64, ), samples=50, optimization_max_steps=500, round_to_powers_of_two=True) if __name__ == '__main__': absltest.main()

[ "copybara-worker@google.com" ]

copybara-worker@google.com

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/moodledata/vpl_data/380/usersdata/315/99246/submittedfiles/principal.py

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[]

no_license

rafaelperazzo/programacao-web

95643423a35c44613b0f64bed05bd34780fe2436

170dd5440afb9ee68a973f3de13a99aa4c735d79

refs/heads/master

2021-01-12T14:06:25.773146

2017-12-22T16:05:45

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# -*- coding: utf-8 -*- from minha_bib import * #COMECE AQUI ABAIXO matriz = [[' ',' ',' '],[' ',' ',' '],[' ',' ',' ']] print (matriz[0][0] + '|' + matriz[0][1] + '|' + matriz[0][2]) matriz[0][0] = input('dgite sua jogada: ') print (matriz[0][0] + '|' + matriz[0][1] + '|' + matriz[0][2])

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

rafael.mota@ufca.edu.br

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2022-10-16T19:04:15.733439

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#! /usr/bin/env python3 # -*- coding: utf-8 -*- # Copyright 2019 Kyoto University (Hirofumi Inaguma) # Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0) """Select an decoder network.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function def build_decoder(args, special_symbols, enc_n_units, vocab, ctc_weight, ctc_fc_list, global_weight, external_lm=None): if args.dec_type in ['transformer', 'transformer_xl']: from neural_sp.models.seq2seq.decoders.transformer import TransformerDecoder decoder = TransformerDecoder( special_symbols=special_symbols, enc_n_units=enc_n_units, attn_type=args.transformer_attn_type, n_heads=args.transformer_n_heads, n_layers=args.dec_n_layers, d_model=args.transformer_d_model, d_ff=args.transformer_d_ff, d_ff_bottleneck_dim=getattr(args, 'transformer_d_ff_bottleneck_dim', 0), layer_norm_eps=args.transformer_layer_norm_eps, ffn_activation=args.transformer_ffn_activation, pe_type=args.transformer_dec_pe_type, vocab=vocab, tie_embedding=args.tie_embedding, dropout=args.dropout_dec, dropout_emb=args.dropout_emb, dropout_att=args.dropout_att, dropout_layer=args.dropout_dec_layer, dropout_head=args.dropout_head, lsm_prob=args.lsm_prob, ctc_weight=ctc_weight, ctc_lsm_prob=args.ctc_lsm_prob, ctc_fc_list=ctc_fc_list, backward=(dir == 'bwd'), global_weight=global_weight, mtl_per_batch=args.mtl_per_batch, param_init=args.transformer_param_init, memory_transformer=args.dec_type == 'transformer_xl', mem_len=args.mem_len, mocha_chunk_size=args.mocha_chunk_size, mocha_n_heads_mono=args.mocha_n_heads_mono, mocha_n_heads_chunk=args.mocha_n_heads_chunk, mocha_init_r=args.mocha_init_r, mocha_eps=args.mocha_eps, mocha_std=args.mocha_std, mocha_no_denominator=args.mocha_no_denominator, mocha_1dconv=args.mocha_1dconv, mocha_quantity_loss_weight=args.mocha_quantity_loss_weight, mocha_head_divergence_loss_weight=args.mocha_head_divergence_loss_weight, latency_metric=args.mocha_latency_metric, latency_loss_weight=args.mocha_latency_loss_weight, mocha_first_layer=args.mocha_first_layer, share_chunkwise_attention=getattr(args, 'share_chunkwise_attention', False), external_lm=external_lm, lm_fusion=args.lm_fusion) elif args.dec_type in ['lstm_transducer', 'gru_transducer']: from neural_sp.models.seq2seq.decoders.rnn_transducer import RNNTransducer decoder = RNNTransducer( special_symbols=special_symbols, enc_n_units=enc_n_units, rnn_type=args.dec_type, n_units=args.dec_n_units, n_projs=args.dec_n_projs, n_layers=args.dec_n_layers, bottleneck_dim=args.dec_bottleneck_dim, emb_dim=args.emb_dim, vocab=vocab, dropout=args.dropout_dec, dropout_emb=args.dropout_emb, lsm_prob=args.lsm_prob, ctc_weight=ctc_weight, ctc_lsm_prob=args.ctc_lsm_prob, ctc_fc_list=ctc_fc_list, external_lm=external_lm if args.lm_init else None, global_weight=global_weight, mtl_per_batch=args.mtl_per_batch, param_init=args.param_init) else: from neural_sp.models.seq2seq.decoders.las import RNNDecoder decoder = RNNDecoder( special_symbols=special_symbols, enc_n_units=enc_n_units, rnn_type=args.dec_type, n_units=args.dec_n_units, n_projs=args.dec_n_projs, n_layers=args.dec_n_layers, bottleneck_dim=args.dec_bottleneck_dim, emb_dim=args.emb_dim, vocab=vocab, tie_embedding=args.tie_embedding, attn_type=args.attn_type, attn_dim=args.attn_dim, attn_sharpening_factor=args.attn_sharpening_factor, attn_sigmoid_smoothing=args.attn_sigmoid, attn_conv_out_channels=args.attn_conv_n_channels, attn_conv_kernel_size=args.attn_conv_width, attn_n_heads=args.attn_n_heads, dropout=args.dropout_dec, dropout_emb=args.dropout_emb, dropout_att=args.dropout_att, lsm_prob=args.lsm_prob, ss_prob=args.ss_prob, ss_type=args.ss_type, ctc_weight=ctc_weight, ctc_lsm_prob=args.ctc_lsm_prob, ctc_fc_list=ctc_fc_list, mbr_training=args.mbr_training, mbr_ce_weight=args.mbr_ce_weight, external_lm=external_lm, lm_fusion=args.lm_fusion, lm_init=args.lm_init, backward=(dir == 'bwd'), global_weight=global_weight, mtl_per_batch=args.mtl_per_batch, param_init=args.param_init, mocha_chunk_size=args.mocha_chunk_size, mocha_n_heads_mono=args.mocha_n_heads_mono, mocha_init_r=args.mocha_init_r, mocha_eps=args.mocha_eps, mocha_std=args.mocha_std, mocha_no_denominator=args.mocha_no_denominator, mocha_1dconv=args.mocha_1dconv, mocha_quantity_loss_weight=args.mocha_quantity_loss_weight, latency_metric=args.mocha_latency_metric, latency_loss_weight=args.mocha_latency_loss_weight, gmm_attn_n_mixtures=args.gmm_attn_n_mixtures, replace_sos=args.replace_sos, distillation_weight=args.distillation_weight, discourse_aware=args.discourse_aware) return decoder

[ "hiro.mhbc@gmail.com" ]

hiro.mhbc@gmail.com

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/bird_sight.py

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[]

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rohanpahwa1/hacker_rank_solutions

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def count(li): maxcount,maxvalue=0,0 for i in li: count=0 for j in range(len(li)): if li[j]==li[i]: count=count+1 if count>maxcount: maxcount=count maxvalue=li[i] return maxvalue n=int(input()) li=list(map(int,input().split())) print(count(li))

[ "coderrohanpahwa@gmail.com" ]

coderrohanpahwa@gmail.com

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2021-01-16T22:03:50.193700

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import datetime from django.db import models from django.conf import settings from django.contrib.sites.models import Site from django.utils.translation import ugettext_lazy as _ CONTACTME_MSG_MAX_LEN = getattr(settings,'CONTACTME_MSG_MAX_LEN',3000) class ContactMsg(models.Model): """ An incoming message from a site visitor. """ site = models.ForeignKey(Site) name = models.CharField(_("Contact's name"), max_length=100) email = models.EmailField(_("Contact's email address")) message = models.TextField(_("Message"), max_length=CONTACTME_MSG_MAX_LEN) submit_date = models.DateTimeField(_("Date/Time submitted"), default=None) ip_address = models.IPAddressField(_('IP address'), blank=True, null=True) class Meta: db_table = "contactme_contact_msg" ordering = ('submit_date',) verbose_name = _('contact message') verbose_name_plural = _('contact messages') def __unicode__(self): return "%s: %s..." % (self.name, self.message[:50]) def save(self, *args, **kwargs): if self.submit_date is None: self.submit_date = datetime.datetime.now() super(ContactMsg, self).save(*args, **kwargs) def get_as_text(self): """ Return this comment as plain text. Useful for emails. """ d = { 'user': self.name, 'date': self.submit_date, 'message': self.message, 'domain': self.site.domain, } return _('Sent by %(user)s at %(date)s\n\n%(message)s\n\nhttp://%(domain)s') % d

[ "danirus@eml.cc" ]

danirus@eml.cc

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stasvorosh/pythonintask

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2021-01-17T16:49:32.778063

2016-10-10T14:08:04

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2016-02-22T07:33:16

2016-02-22T07:33:15

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# Задача 1. Вариант 21. #Напишите программу, которая будет сообщать род деятельности и псевдоним под которым скрывается Михаил Николаевич Румянцев. После вывода информации программа должна дожидаться пока пользователь нажмет Enter для выхода. # Platonova O. A. # 29.05.2016 print("Михаил Николаевич Румянцев более известен, как клоун Карандаш.") input("\n\nНажмите Enter для выхода.")

[ "stasyan.v@gmail.com" ]

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/Leetcode/0151-0200/0169-majority-element.py

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MiKueen/Data-Structures-and-Algorithms

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2021-07-18T17:16:39.948239

2020-09-13T15:44:37

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''' Author : MiKueen Level : Easy Problem Statement : Majority Element Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊ n/2 ⌋ times. You may assume that the array is non-empty and the majority element always exist in the array. Example 1: Input: [3,2,3] Output: 3 Example 2: Input: [2,2,1,1,1,2,2] Output: 2 ''' class Solution: def majorityElement(self, nums: List[int]) -> int: mapping = {} for i in nums: if i not in mapping: mapping[i] = 1 if mapping[i] > len(nums) // 2: return i else: mapping[i] += 1

[ "keshvi2298@gmail.com" ]

keshvi2298@gmail.com

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2020-04-26T15:01:42.644950

2019-10-10T14:05:18

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""" Django settings for DMVProject project. Generated by 'django-admin startproject' using Django 2.0.6. For more information on this file, see https://docs.djangoproject.com/en/2.0/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.0/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.0/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = '5_f4_(jx%bakt6_a8q9*^(a1@cblb(x&jvs=vep+1-8eukn^5d' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'DMVApp', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'DMVProject.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'DMVProject.wsgi.application' # Database # https://docs.djangoproject.com/en/2.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/2.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.0/howto/static-files/ STATIC_URL = '/static/'

[ "kenn+git@code-crew.org" ]

kenn+git@code-crew.org

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/python_workout/01_numeric_types/number_guessing_game/!python3 number_guessing_game.py

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paulghaddad/solve-it

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refs/heads/master

2023-01-24T03:46:24.285793

2021-07-06T19:44:29

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import random def start_game(): number_to_guess = random.randint(0, 100) print(number_to_guess) if __name__ == '__main__': start_game()

[ "paulh16@gmail.com" ]

paulh16@gmail.com

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/google/ads/googleads/v7/googleads-py/google/ads/googleads/v7/errors/types/language_code_error.py

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2023-07-17T22:11:47.848185

2021-08-29T20:39:47

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# -*- coding: utf-8 -*- # Copyright 2020 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 # # 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 proto # type: ignore __protobuf__ = proto.module( package='google.ads.googleads.v7.errors', marshal='google.ads.googleads.v7', manifest={ 'LanguageCodeErrorEnum', }, ) class LanguageCodeErrorEnum(proto.Message): r"""Container for enum describing language code errors. """ class LanguageCodeError(proto.Enum): r"""Enum describing language code errors.""" UNSPECIFIED = 0 UNKNOWN = 1 LANGUAGE_CODE_NOT_FOUND = 2 INVALID_LANGUAGE_CODE = 3 __all__ = tuple(sorted(__protobuf__.manifest))

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bazel-bot-development[bot]@users.noreply.github.com

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shihao-zhang/buildsimhub_python_api

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2020-03-28T02:40:34.693984

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""" AUTHOR: Tracy Ruan Date: 6/30/2018 What is this script for? This script extract results from a parametric study from BuildSimCloud, and then use the results to train a random forest tree model. The training accuracy will be demonstrated by MAE and MAPE, and predicted vs. actual plot will be used for comparison. How to use this script? Replace the project_api_key and model_api_key in this script. Make sure that the model_api_key is the one provided after a successful parametric run. Specify the number of trees in the forest (n_estimate) Package required: pandas, numpy, sci-kit learn, matplotlib """ import BuildSimHubAPI as bsh_api import pandas as pd import numpy as np from sklearn.model_selection import train_test_split from sklearn.ensemble import RandomForestRegressor import matplotlib.pyplot as plt """ User Input """ project_api_key = 'f98aadb3-254f-428d-a321-82a6e4b9424c' model_api_key = 'aa09eabf-693f-4437-88cc-a522a25fba01' # The number of trees in the forest. n_estimate = 1000 """ Script """ bsh = bsh_api.BuildSimHubAPIClient() results = bsh.parametric_results(project_api_key, model_api_key) # Collect results result_dict = results.net_site_eui() result_unit = results.last_parameter_unit for i in range(len(result_dict)): tempstr = result_dict["value"] dict = {} for key in result_dict: if key == "model": templist = result_dict[key] tempdict = {} for i in range(len(templist)): tempstr = result_dict["model"][i] templist = tempstr.split(',') for j in range(len(templist)): pair = templist[j].split(': ') if pair[0] not in tempdict: tempdict[pair[0]] = [] tempdict[pair[0]].append(pair[1]) for subkey in tempdict: dict[subkey] = tempdict[subkey] else: dict[key] = result_dict[key] df = pd.DataFrame(dict) values = np.array(df['value']) # axis 1 refers to the columns features_old = df.drop('value', axis=1) features = features_old.drop('model_plot', axis=1) feature_list = list(features.columns) features = np.array(features) print(feature_list) # Split the data into training and testing sets train_features, test_features, train_values, test_values = train_test_split(features, values) # train models rf = RandomForestRegressor(n_estimators=n_estimate) rf.fit(train_features, train_values) # predict values using rf on test data predictions = rf.predict(test_features) # Calculate the absolute errors errors = abs(predictions - test_values) # mean absolute error (MAE) is a measure of difference between two continuous variables print('Mean Absolute Error:', round(np.mean(errors), 2), 'degrees.') # Determine Performance Metrics # Calculate mean absolute percentage error (MAPE) mape = 100 * (errors / test_values) accuracy = 100 - np.mean(mape) print('Accuracy:', round(accuracy, 2), '%.') # Actual value VS predicted value plot plt.scatter(test_values, predictions, s=1) plt.plot([min(test_values), max(test_values)], [min(predictions), max(predictions)], 'red', linewidth=1) plt.ylabel('Actual Value') plt.xlabel('Predicted Value') plt.title('Actual VS Predicted') plt.show()

[ "weilix@alumni.cmu.edu" ]

weilix@alumni.cmu.edu

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Koshir0/CS50-WEB-PROGRAMMING-PROJECTS

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# Generated by Django 3.0.8 on 2020-08-23 15:21 import datetime from django.conf import settings from django.db import migrations, models from django.utils.timezone import utc class Migration(migrations.Migration): dependencies = [ ('network', '0014_auto_20200823_1047'), ] operations = [ migrations.DeleteModel( name='Person', ), migrations.AlterField( model_name='follower', name='users', field=models.ManyToManyField(blank=True, related_name='following', to=settings.AUTH_USER_MODEL), ), migrations.AlterField( model_name='post', name='created_date', field=models.DateTimeField(default=datetime.datetime(2020, 8, 23, 15, 21, 45, 798323, tzinfo=utc)), ), ]

[ "pentiumdesu@protonmail.com" ]

pentiumdesu@protonmail.com

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no_license

JosephLevinthal/Research-projects

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refs/heads/master

2022-07-31T06:43:02.686109

2020-05-23T00:24:26

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nA = int(input("Numero de habitantes da cidade A:")) nB = int(input("Numero de habitantes da cidade B:")) pA = float(input("Percentual de crescimento populacional da cidade A:")) pB = float(input("Percentual de crescimento populacional da cidade B:")) pA = pA/100 pB = pB/100 ano = 0 while(nA < nB): nA = nA + nA*pA nB = nB + nB*pB ano = ano + 1 print(ano)

[ "jvlo@icomp.ufam.edu.br" ]

jvlo@icomp.ufam.edu.br

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/src/python/WMCore/PilotManager/plugin/PilotLSFSubmitter.py

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[]

no_license

sryufnal/WMCore

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refs/heads/master

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from ProdAgent.Resources.LSF import LSFConfiguration from PilotManager.CommonUtil import executeCommand #from JobSubmitter.Submitters.BulkSubmitterInterface import makeNonBlocking from JobSubmitter.JSException import JSException import datetime import logging import sys import os class PilotLSFSubmitter: def __init__(self): pass def submitPilot(self, taskName, exe, exePath, inputSandbox): shellScript = exe scriptPath = exePath #start lsf submission command lsfSubmitCommand = 'bsub' #TODO: read this info from configuration lsfSubmitCommand += ' -q 8nh80 ' #creating the log directory. #TODO: get the path information from the configuration lsfLogDir = '/afs/cern.ch/user/k/khawar/scratch2/khawar/logs' if ( lsfLogDir != 'None' ): now = datetime.datetime.today() lsfLogDir += '/%s' % now.strftime("%Y%m%d%H") try: os.mkdir(lsfLogDir) logging.debug("Created directory %s" % lsfLogDir) except OSError, err: # suppress LSF log unless it's about an already exisiting directory if err.errno != errno.EEXIST or not os.path.isdir(lsfLogDir): logging.debug("Can't create directory %s, turning off LSF log" % lsfLogDir) lsfLogDir = 'None' lsfSubmitCommand += ' -g %s' % LSFConfiguration.getGroup() if ( lsfLogDir == "None" ): lsfSubmitCommand += ' -oo /dev/null' else: lsfSubmitCommand += ' -oo %s/%s.lsf.log' % (lsfLogDir,'pilot') lsfSubmitCommand += ' < %s' % os.path.join(scriptPath, shellScript) failureList = [] try: output = executeCommand(lsfSubmitCommand) logging.info("PilotManager.submitPilotJob: %s " % output) logging.info("PilotManager.submitPilotJob: %s " %lsfSubmitCommand ) except RuntimeError, err: failureList.append('jobSpec') if len(failureList) > 0: raise JSException("Submission Failed", FailureList = failureList)

[ "metson@4525493e-7705-40b1-a816-d608a930855b" ]

metson@4525493e-7705-40b1-a816-d608a930855b

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/zinnia/markups.py

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[ "BSD-3-Clause" ]

permissive

lpe234/django-blog-zinnia

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refs/heads/develop

2021-01-16T21:31:06.297887

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BSD-3-Clause

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""" Set of" markup" function to transform plain text into HTML for Zinnia. Code originally provided by django.contrib.markups """ import warnings from django.utils.encoding import force_text from django.utils.encoding import force_bytes from zinnia.settings import MARKDOWN_EXTENSIONS from zinnia.settings import RESTRUCTUREDTEXT_SETTINGS def textile(value): """ Textile processing. """ try: import textile except ImportError: warnings.warn("The Python textile library isn't installed.", RuntimeWarning) return value return textile.textile(force_bytes(value), encoding='utf-8', output='utf-8') def markdown(value, extensions=MARKDOWN_EXTENSIONS): """ Markdown processing with optionally using various extensions that python-markdown supports. """ try: import markdown except ImportError: warnings.warn("The Python markdown library isn't installed.", RuntimeWarning) return value extensions = [e for e in extensions.split(',') if e] return markdown.markdown(force_text(value), extensions, safe_mode=False) def restructuredtext(value, settings=RESTRUCTUREDTEXT_SETTINGS): """ RestructuredText processing with optionnally custom settings. """ try: from docutils.core import publish_parts except ImportError: warnings.warn("The Python docutils library isn't installed.", RuntimeWarning) return value parts = publish_parts(source=force_bytes(value), writer_name='html4css1', settings_overrides=settings) return force_text(parts['fragment'])

[ "fantomas42@gmail.com" ]

fantomas42@gmail.com

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/rllib/agents/marwil/marwil_torch_policy.py

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permissive

ray-project/maze-raylit

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refs/heads/master

2023-01-23T04:23:35.178501

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import ray from ray.rllib.agents.marwil.marwil_tf_policy import postprocess_advantages from ray.rllib.evaluation.postprocessing import Postprocessing from ray.rllib.policy.sample_batch import SampleBatch from ray.rllib.policy.torch_policy_template import build_torch_policy from ray.rllib.utils.framework import try_import_torch from ray.rllib.utils.torch_ops import explained_variance torch, _ = try_import_torch() class ValueNetworkMixin: def __init__(self): def value(ob, prev_action, prev_reward, *state): model_out, _ = self.model({ SampleBatch.CUR_OBS: torch.Tensor([ob]).to(self.device), SampleBatch.PREV_ACTIONS: torch.Tensor([prev_action]).to( self.device), SampleBatch.PREV_REWARDS: torch.Tensor([prev_reward]).to( self.device), "is_training": False, }, [torch.Tensor([s]).to(self.device) for s in state], torch.Tensor([1]).to(self.device)) return self.model.value_function()[0] self._value = value def marwil_loss(policy, model, dist_class, train_batch): model_out, _ = model.from_batch(train_batch) action_dist = dist_class(model_out, model) state_values = model.value_function() advantages = train_batch[Postprocessing.ADVANTAGES] actions = train_batch[SampleBatch.ACTIONS] # Value loss. policy.v_loss = 0.5 * torch.mean(torch.pow(state_values - advantages, 2.0)) # Policy loss. # Advantage estimation. adv = advantages - state_values # Update averaged advantage norm. policy.ma_adv_norm.add_( 1e-6 * (torch.mean(torch.pow(adv, 2.0)) - policy.ma_adv_norm)) # #xponentially weighted advantages. exp_advs = torch.exp(policy.config["beta"] * (adv / (1e-8 + torch.pow(policy.ma_adv_norm, 0.5)))) # log\pi_\theta(a|s) logprobs = action_dist.logp(actions) policy.p_loss = -1.0 * torch.mean(exp_advs.detach() * logprobs) # Combine both losses. policy.total_loss = policy.p_loss + policy.config["vf_coeff"] * \ policy.v_loss explained_var = explained_variance(advantages, state_values) policy.explained_variance = torch.mean(explained_var) return policy.total_loss def stats(policy, train_batch): return { "policy_loss": policy.p_loss, "vf_loss": policy.v_loss, "total_loss": policy.total_loss, "vf_explained_var": policy.explained_variance, } def setup_mixins(policy, obs_space, action_space, config): # Create a var. policy.ma_adv_norm = torch.tensor( [100.0], dtype=torch.float32, requires_grad=False).to(policy.device) # Setup Value branch of our NN. ValueNetworkMixin.__init__(policy) MARWILTorchPolicy = build_torch_policy( name="MARWILTorchPolicy", loss_fn=marwil_loss, get_default_config=lambda: ray.rllib.agents.marwil.marwil.DEFAULT_CONFIG, stats_fn=stats, postprocess_fn=postprocess_advantages, before_loss_init=setup_mixins, mixins=[ValueNetworkMixin])

[ "noreply@github.com" ]

ray-project.noreply@github.com

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/LESSON2b/.history/backend/app_20200531173010.py

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[]

no_license

hiyacins/uma_study

c329d29a9c3899ab4feca21b9c47ef546b69b0bd

067e66f258a0c89f7670c645dd7c40feee8536fa

refs/heads/master

2023-01-23T06:40:12.435047

2020-06-17T15:59:34

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0

null

2023-01-06T08:36:26

2020-02-08T05:56:52

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UTF-8

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py

from HiyaLib import * import unittest from flask import Flask, render_template # app = FlaskBuilder(__name__) app = Flask(__name__, static_folder='../frontend/dist/static', template_folder='../frontend/dist') @app.route('/', defaults={'path': ''}) @app.route('/<path:path>') def index(path): print('umauma') return render_template('index.html') if __name__ == "__main__": app.run(port=5001, debug=True) # app.run(host="0.0.0.0", port=80, debug=False) # unittest.main()

[ "hiyacins@gmail.com" ]

hiyacins@gmail.com

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/bscan/wordlists.py

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[ "MIT" ]

permissive

raystyle/bscan

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refs/heads/master

2020-04-25T03:15:37.186913

2019-02-09T22:23:44

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"""Utilities for dealing with wordlists.""" import fnmatch import os from typing import ( List) def find_wordlist(wordlist_dirs: List[str], fnpattern: str) -> None: """Recursively search wordlist directories for a specified filename.""" for wordlist_dir in wordlist_dirs: _walk_iter = os.walk(wordlist_dir, followlinks=True) for dirpath, dirnames, filenames in _walk_iter: for match in fnmatch.filter(filenames, fnpattern): print(os.path.join(dirpath, match)) def walk_wordlists(wordlist_dirs: List[str]) -> None: """Recursively walk the wordlist directories and print all files.""" for wordlist_dir in wordlist_dirs: _walk_iter = os.walk(wordlist_dir, followlinks=True) for dirpath, dirnames, filenames in _walk_iter: if not filenames: continue print(dirpath) for filename in filenames: print(filename) print()

[ "welch18@vt.edu" ]

welch18@vt.edu

dc9eda48d4dbd451dc8477cffc39ad159ec15d1c

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/xpath_01.py

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[]

no_license

patronsbai/scrapy_spider

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refs/heads/master

2021-05-03T09:20:03.247818

2018-03-08T15:26:16

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UTF-8

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# -*- coding:utf-8 -*- import urllib from lxml import etree # def getHtml(url): # page = urllib.urlopen(url) # html = page.read() # return html if __name__ == '__main__': # text = getHtml("http://image.baidu.com/search/index?tn=baiduimage&ct=201326592&lm=-1&cl=2&ie=gbk&word=%CD%BC%C6%AC&fr=ala&ala=1&alatpl=others&pos=0") # print text text = ''' <div> <ul> <li class="item-0"><a href="link1.html">first item</a></li> <li class="item-1"><a href="link2.html">second item</a></li> <li class="item-inactive"><a href="link31111.html">third item</a></li> <li class="item-1"><a href="link4.html">fourth item</a></li> <li class="item-0"><a href="link5.html">fifth item</a> </ul> </div> ''' # 1.转换成 lxml文档 html_data = etree.HTML(text) # 2. 格式化 # html_result = etree.tostring(html_data) # print html_result # # #3.4 取出属性的值 # < li class ="item-inactive" > < a href="link3.html" > third item < / a > < / li > result = html_data.xpath('//li[@class="item-inactive"]/a/@href') # result = html_data.xpath('//*[@id="imgid"]/div/ul/li[2]/div/a/img') print result # # #3.5 模糊查询 contains # result1 = html_data.xpath('//li[contains(@class,"1")]') # # print result1 # print html_result #3.掌握的 xpath #3.1取出所有的li标签 # result = html_data.xpath('//li') #3.2获取所有a # result = html_data.xpath('//li/a') # # #3.3 取出内容 # result = html_data.xpath('//li/a/text()') #

[ "xwp_fullstack@163.com" ]

xwp_fullstack@163.com

f5537afaebec1f8d42eb3ac71b04ea9338c4537e

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/python/atpic/wikinormalizer.py

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[]

no_license

alexmadon/atpic_photosharing

7829118d032344bd9a67818cd50e2c27a228d028

9fdddeb78548dadf946b1951aea0d0632e979156

refs/heads/master

2020-06-02T15:00:29.282979

2017-06-12T17:09:52

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null

UTF-8

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py

#!/usr/bin/python3 import atpic.log xx=atpic.log.setmod("INFO","wikinormalizer") """ Used to normalize the wiki URLs we lowercase, replace white spaces with underscore _ This is important as this the key that is used to store/retrieve wiki pages. """ # may need a permanent redirect to avoid ronts indexing several times one page import atpic.normal def normalize(s): s=atpic.normal.remove_diacritics(s) s=s.lower() s=s.replace(b' ',b'_') return s if __name__ == "__main__": print('hi') inputs=( b'FTP', b'File Upload', b'go-go', b'Europe/France' ) for s in inputs: n=normalize(s) print(s,'->',n)

[ "alex.madon@gmail.com" ]

alex.madon@gmail.com

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/hop.py

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[]

no_license

SleepyBag/MNSC

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efc5ec9ddf2faf743585aed1b9371f1af8ee24df

refs/heads/master

2020-04-07T16:31:57.422796

2019-01-09T12:40:20

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null

UTF-8

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false

1,114

py

from collections import Iterable import tensorflow as tf from attention import attention def hop(scope, last, sentence, sentence_bkg, bkg_iter, bkg_fix, doc_len, real_max_len, convert_flag, biases_initializer=tf.initializers.zeros(), weights_initializer=tf.contrib.layers.xavier_initializer()): if not isinstance(bkg_fix, Iterable): bkg_fix = [bkg_fix] bkg_fix = list(bkg_fix) hidden_size = sentence_bkg.shape[2] with tf.variable_scope(scope): sentence = tf.stop_gradient(sentence) \ if not last else sentence sentence_bkg = tf.stop_gradient(sentence_bkg) \ if not last else sentence_bkg alphas = attention(sentence_bkg, [bkg_iter] + bkg_fix, doc_len, real_max_len, biases_initializer=biases_initializer, weights_initializer=weights_initializer) new_bkg = tf.matmul(alphas, sentence_bkg) new_bkg = tf.reshape(new_bkg, [-1, hidden_size], name='new_bkg') if 'o' in convert_flag: new_bkg = bkg_iter + new_bkg return new_bkg

[ "xueqianming200@gmail.com" ]

xueqianming200@gmail.com

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/recipes/gcc/all/test_v1_package/conanfile.py

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[ "MIT" ]

permissive

conan-io/conan-center-index

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refs/heads/master

2023-08-31T11:34:45.403978

2023-08-31T11:13:23

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from conans import ConanFile, tools import os class TestPackageConan(ConanFile): settings = "os", "compiler", "build_type", "arch" generators = "cmake" def test(self): def chmod_plus_x(name): if os.name == 'posix': os.chmod(name, os.stat(name).st_mode | 0o111) cc = self.deps_env_info["gcc"].CC cxx = self.deps_env_info["gcc"].CXX hello_c = os.path.join(self.source_folder, "hello.c") hello_cpp = os.path.join(self.source_folder, "hello.cpp") self.run("%s --version" % cc, run_environment=True) self.run("%s --version" % cxx, run_environment=True) self.run("%s -dumpversion" % cc, run_environment=True) self.run("%s -dumpversion" % cxx, run_environment=True) self.run("%s %s -o hello_c" % (cc, hello_c), run_environment=True) self.run("%s %s -o hello_cpp" % (cxx, hello_cpp), run_environment=True) if not tools.cross_building(self.settings): chmod_plus_x("hello_c") chmod_plus_x("hello_cpp") self.run("./hello_c", run_environment=True) self.run("./hello_cpp", run_environment=True) if tools.which("readelf"): self.run("readelf -l hello_c", run_environment=True) self.run("readelf -l hello_cpp", run_environment=True) if tools.which("otool"): self.run("otool -L hello_c", run_environment=True) self.run("otool -L hello_cpp", run_environment=True)

[ "noreply@github.com" ]

conan-io.noreply@github.com

9555111af343a9c31ab6d5bf143cfb3904d4ca63

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/mv.py

efffb2d694411511f2c57d09aa76b1f6b2a739af

[]

no_license

houking-can/GenDataset

a42388129fb7a5b1c176e77dd953f5fa27e77e7a

fb2e9d841ba0f3288e5152c97e250f709cd4f785

refs/heads/master

2020-05-05T09:48:47.334267

2019-04-26T15:18:12

179,918,151

2

0

null

UTF-8

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py

import os import json import shutil def iter_files(path): """Walk through all files located under a root path.""" if os.path.isfile(path): yield path elif os.path.isdir(path): for dirpath, _, filenames in os.walk(path): for f in filenames: yield os.path.join(dirpath, f) else: raise RuntimeError('Path %s is invalid' % path) path = r'E:\ARXIV' for file in iter_files(path): paper= json.load(open(file)) a= len(' '.join(paper['abstract'])) b= len(' '.join(paper['article'])) c=len(' '.join(paper['conclusion'])) if a>c+b+50: shutil.move(file,r'E:\tmp\arxiv') print(file)

[ "1240723224@qq.com" ]

1240723224@qq.com

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/localizacion/inte_project_invoice_customer/__manifest__.py

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[]

no_license

grudiver/biumak

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refs/heads/master

2022-04-11T13:17:33.347975

2020-03-24T17:55:24

null

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null

UTF-8

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py

# coding: utf-8 ############################################################################## # # Copyright (c) 2016 Tecnología y Servicios AMN C.A. (http://tysamnca.com/) All Rights Reserved. # <contacto@tysamnca.com> # <Teléfono: +58(212) 237.77.53> # Caracas, Venezuela. # # Colaborador: Nathaly Partidas <npartidas@tysamnca.com> # # WARNING: This program as such is intended to be used by professional # programmers who take the whole responsability of assessing all potential # consequences resulting from its eventual inadequacies and bugs # End users who are looking for a ready-to-use solution with commercial # garantees and support are strongly adviced to contract a Free Software # Service Company # # This program is Free Software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. # ############################################################################## { 'name': 'Add project in invoice customer', 'version': '1.0', 'category': 'invoice', 'summary': 'Add project in invoice customer', 'description': """ Add project in invoice customer ===================== Add project in invoice customer """, 'author': 'TYSAMNCA', 'website': 'https://tysamnca.com', 'depends': ['base','account'], 'data': [ 'view/invoice_view.xml' ], #'demo': [], #'test': [], 'installable': True, 'auto_install': False, 'application': False, }

[ "soporte.innova2129@gmail.com" ]

soporte.innova2129@gmail.com

d89f82d820f1cc4b67d71786f096d13e1a94b79b

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/all_data/exercism_data/python/bob/709325c321084d4eaaf1af19e2ad7def.py

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[]

no_license

itsolutionscorp/AutoStyle-Clustering

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be0e2f635a7558f56c61bc0b36c6146b01d1e6e6

refs/heads/master

2020-12-11T07:27:19.291038

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def hey(sentence): if does_not_say_anything(sentence): return 'Fine. Be that way!' if is_a_question(sentence): return 'Sure.' if is_yelling(sentence): return 'Woah, chill out!' return 'Whatever.' def does_not_say_anything(sentence): return sentence.strip() == "" def is_a_question(sentence): return sentence and not is_yelling(sentence) and sentence[-1] == "?" def is_yelling(sentence): return sentence.isupper()

[ "rrc@berkeley.edu" ]

rrc@berkeley.edu

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/python/DeepSeaVectorDraw/FileOrData.py

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permissive

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refs/heads/master

2023-08-31T23:45:19.533393

2023-08-29T07:30:36

2023-08-29T07:30:43

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null

UTF-8

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false

179

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# automatically generated by the FlatBuffers compiler, do not modify # namespace: DeepSeaVectorDraw class FileOrData(object): NONE = 0 FileReference = 1 RawData = 2

[ "akb825@gmail.com" ]

akb825@gmail.com

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/tests/unit/test_clang.py

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[ "NCSA" ]

permissive

blep/Beye

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2021-01-18T13:18:20.381010

2015-06-15T13:46:14

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null

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false

993

py

# -*- coding: utf-8 -*- # The LLVM Compiler Infrastructure # # This file is distributed under the University of Illinois Open Source # License. See LICENSE.TXT for details. import libscanbuild.clang as sut from . import fixtures import os.path class GetClangArgumentsTest(fixtures.TestCase): def test_get_clang_arguments(self): with fixtures.TempDir() as tmpdir: filename = os.path.join(tmpdir, 'test.c') with open(filename, 'w') as handle: handle.write('') result = sut.get_arguments( tmpdir, ['clang', '-c', filename, '-DNDEBUG', '-Dvar="this is it"']) self.assertIn('NDEBUG', result) self.assertIn('var="this is it"', result) def test_get_clang_arguments_fails(self): self.assertRaises( Exception, sut.get_arguments, '.', ['clang', '-###', '-fsyntax-only', '-x', 'c', 'notexist.c'])

[ "rizsotto@gmail.com" ]

rizsotto@gmail.com

2f903fb6b05308a81d77262030e3009f2320f061

f68732bc40a7a90c3a1082e4b3a4154518acafbb

/script/dbus/sessionBus/timedate/007_setDate.py

b177277e1d4c004f8660ca893111b67f56b2ef9f

[]

no_license

lizhouquan1017/dbus_demo

94238a2307e44dabde9f4a4dd0cf8ec217260867

af8442845e722b258a095e9a1afec9dddfb175bf

refs/heads/master

2023-02-11T19:46:27.884936

2021-01-08T05:27:18

327,162,635

0

null

UTF-8

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false

1,077

py

# -*- coding: utf-8 -*- # **************************************************** # @Test Case ID: 007_setDate # @Test Description: 设置系统时间和日期 # @Test Condition: 关闭时间自动同步设置 # @Test Step: 1.重置系统时间和网络时间同步； # @Test Result: 1.检查重置成功; # @Test Remark: # @Author: ut000511 # ***************************************************** import time import pytest from frame.base import OSBase from aw.dbus.sessionBus import timedate class TestCase(OSBase): def setUp(self): self.Step("预制条件1:关闭时间自动同步设置") timedate.setNTP(False) @pytest.mark.public def test_step(self): self.Step("步骤1:设置系统时间和日期") timedate.setDate(2020, 7, 28, 10, 30, 10, 0) self.CheckPoint("检查点1: 检查时间设置成功") timedate.checkSetDateStatus(7, 28) def tearDown(self): self.Step("收尾:还原系统时间设置") time.sleep(2) timedate.reset()

[ "lizhouquan@uniontech.com" ]

lizhouquan@uniontech.com

7703332074976cd837f06a01e576212613255699

7b51c2248463406783e18f6bc02e2e6ef68aecb2

/agol_util.py

5bb206e400524b0281b1b209c773956956682f63

[]

no_license

fgassert/agol_util

88712974720103826f9d21136a6612b6aa67a806

cc8c8b9e5915958cafd08d65f9b3361e608a556d

refs/heads/master

2016-09-06T12:51:04.888287

2015-08-04T20:57:43

40,208,668

0

2

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UTF-8

Python

false

4,667

py

import urllib2 import urllib import json import time class AGOL_util: """ Minimal client library for ArcGIS online API Parameters: root_url: portal root rest url e.g. http://myorg.arcgis.com/sharing/rest username: valid arggis online username password: valid arggis online password """ def __init__(self, root_url, username, password): self.url = root_url self._check_items = [] self._uid = username self._pwdd = password self._validate_user(username, password) def _validate_user(self, username, password): ''' Requests token based on username and password no error catching ''' keys = {'username':username, 'password':password, 'referer':self.url, 'f':'json'} data = urllib.urlencode(keys) req = urllib2.Request('https://www.arcgis.com/sharing/rest/generateToken', data) resp = json.load(urllib2.urlopen(req)) if 'token' in resp: self._token = resp['token'] self._expiry = resp['expires'] else: self._token = '' self._expiry = 0 return resp def get_token(self, nd=False): """ returns valid token or false on failure """ if self._token=='' or self._expiry <= time.time(): if nd: return False else: self._validate_user(self._uid, self._pwd) return(self.get_token(1)) return self._token def query(self, endpoint, options): ''' POST to url endpoint with options as data autoappends token and json response parameters concatinates self.url and endpoind assuming matching /'s return as JSON ''' options['token'] = self.get_token() options['f'] = 'json' data = urllib.urlencode(options) requrl = "{}{}".format(self.url, endpoint) req = urllib2.Request(requrl, data) return json.load(urllib2.urlopen(req)) def add_item_from_url(self, url, options={}): options['dataUrl'] = url options['async'] = 'true' options['overwrite'] = 'true' return self.query('/content/users/{}/addItem'.format(self._uid), options) def add_shapefile_from_url(self, url, options={}): """ URL should point to zipped shapefile """ options['type'] = 'Shapefile' return self.add_item_from_url(url, options) def get_item_status(self, itemId): url = '/content/users/{}/items/{}/status'.format(self._uid, itemId) return self.query(url, {}) def wait_for_completion(self, itemId, timeout=60): ''' Check every second for item status to return completed Return: true on completion false on timeout or error ''' res = self.get_item_status(itemId) t = 0 while 'status' in res and t < timeout: if res['status'] == 'completed': return True t += 1 time.sleep(1) res = self.get_item_status(itemId) return False def update_item(self, itemId, options): url = '/content/users/{}/items/{}/update'.format(self._uid, itemId) return self.query(url, options) def share_items(self, items, everyone=None, org=None, groups=None): """ shares items defined by item ids with given groups, org, or everyone """ options = {} if groups is not None: options['groups'] = groups if everyone is not None: options['everyone'] = everyone if org is not None: options['org'] = org if type(items) == list: items = ','.join(items) options['items'] = items return self.query('/content/users/{}/shareItems'.format(self._uid), options) def publish_item(self, itemId, options, publishParameters): options['itemID'] = itemId options['publishParameters'] = json.dumps(publishParameters) options['overwrite'] = 'true' return self.query('/content/users/{}/publish'.format(self._uid), options) def publish_shapefile(self, itemId, options={}, publishParameters={}): options['fileType'] = 'shapefile' if 'name' not in publishParameters: publishParameters['name'] = itemId return self.publish_item(itemId, options, publishParameters) def delete_item(self, itemId): url = '/content/users/{}/items/{}/delete'.format(self._uid, itemId) return self.query(url)

[ "cowbox314@gmail.com" ]

cowbox314@gmail.com

25cfefcf5435888d72794db6ffd98d70ec97293a

5dae158ba8adef3a30061336cf24087273d1d1be

/scripts/gpipe/analyze_predictions.py

3744ec4746e1bba27c9c0f8cb81351f3945c9544

[]

no_license

Q-KIM/cgat

595cbc51d0d34f4442d4d124e2fec2be8e1a2a79

3bccc543d3daa1ee8830ecb0467e2b3b3b5beb9a

refs/heads/master

2021-01-17T07:30:00.213178

2015-06-05T14:03:33

null

0

null

UTF-8

Python

false

4,625

py

########################################################################## # # MRC FGU Computational Genomics Group # # $Id$ # # Copyright (C) 2009 Andreas Heger # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. ########################################################################## ''' gpipe/analyze_predictions.py - ====================================================== :Author: Andreas Heger :Release: $Id$ :Date: |today| :Tags: Python Purpose ------- .. todo:: describe purpose of the script. Usage ----- Example:: python gpipe/analyze_predictions.py --help Type:: python gpipe/analyze_predictions.py --help for command line help. Documentation ------------- Code ---- ''' import sys import pgdb import csv import CGAT.Experiment as E def main(argv=None): """script main. parses command line options in sys.argv, unless *argv* is given. """ if argv is None: argv = sys.argv parser = E.OptionParser( version="%prog version: $Id: gpipe/analyze_predictions.py 2781 2009-09-10 11:33:14Z andreas $") parser.add_option("-s", "--species-regex", dest="species_regex", type="string", help="regular expression to extract species from identifier.") parser.add_option("-g", "--gene-regex", dest="gene_regex", type="string", help="regular expression to extract gene from identifier.") parser.add_option("-m", "--methods", dest="methods", type="string", help="methods to use [query|].") parser.set_defaults( species_regex="^([^|]+)\|", gene_regex="^[^|]+\|[^|]+\|([^|]+)\|", methods="query", tablename_predictions="predictions", separator="|") (options, args) = E.Start( parser, add_psql_options=True, add_csv_options=True) options.methods = options.methods.split(",") dbhandle = pgdb.connect(options.psql_connection) fields = [] for method in options.methods: if method == "query": fields += ["query", "lquery"] elif method == "nexons": fields.append("nexons") else: raise "unknown method %s" % method outfile = sys.stdout writer = csv.DictWriter(outfile, fields, dialect=options.csv_dialect, lineterminator=options.csv_lineterminator, extrasaction='ignore') first = True for line in sys.stdin: if line[0] == "#": continue data = line[:-1].split("\t") if first: outfile.write("\t".join(data + fields) + "\n") first = False continue schema, prediction_id, gene_id, quality = data[ 0].split(options.separator) outfile.write(line[:-1]) for method in options.methods: if method == "query": statement = "SELECT query_token, query_length FROM %s.%s WHERE prediction_id = '%s'" % (schema, options.tablename_predictions, prediction_id) elif method == "nexons": statement = "SELECT nintrons+1 FROM %s.%s WHERE prediction_id = '%s'" % (schema, options.tablename_predictions, prediction_id) cc = dbhandle.cursor() cc.execute(statement) rr = cc.fetchone() cc.close() for x in rr: outfile.write("\t%s" % str(x)) outfile.write("\n") E.Stop() if __name__ == "__main__": sys.exit(main(sys.argv))

[ "andreas.heger@gmail.com" ]

andreas.heger@gmail.com

c48eda74cdfae649b3b3e018fce9d41f437ae699

e0d776ec6d324e8630d463a1be81f81ccd3a51a9

/schools/migrations/0001_initial.py

c396d66cea23dd7a30c9e856f2417162a10c14b1

[ "MIT" ]

permissive

moshthepitt/shulezote

9b3c8c6d5c53e2b497977fd6900e500e09315c41

e903a208948ab5294183e2a8c2dac9360a184654

refs/heads/master

2021-07-03T11:17:19.274106

2019-08-04T09:49:59

32,628,463

2

1

MIT

2021-06-10T19:47:39

2015-03-21T10:35:34

Python

UTF-8

Python

false

3,775

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import autoslug.fields import django.contrib.gis.db.models.fields class Migration(migrations.Migration): dependencies = [ ('places', '0001_initial'), ] operations = [ migrations.CreateModel( name='School', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('created_on', models.DateTimeField(auto_now_add=True, verbose_name='Created on')), ('updated_on', models.DateTimeField(auto_now=True, verbose_name='Updated on')), ('code', models.CharField(max_length=255, verbose_name='Code', blank=True)), ('name', models.CharField(max_length=255, verbose_name='Name of School')), ('slug', autoslug.fields.AutoSlugField(unique=True, editable=False)), ('address', models.CharField(max_length=255, verbose_name='Address', blank=True)), ('level', models.CharField(help_text='Primary or secondary school', max_length=1, verbose_name='Level', choices=[(b'1', 'Primary School'), (b'2', 'Secondary School')])), ('school_type', models.CharField(default=b'1', help_text='Day, Boarding or Both?', max_length=1, verbose_name='School Type', choices=[(b'1', 'Day'), (b'2', 'Boarding'), (b'3', 'Day & Boarding')])), ('student_gender', models.CharField(default=b'3', help_text='Boys school, Girls school, or mixed', max_length=1, verbose_name='Student Gender', choices=[(b'1', 'Boys'), (b'2', 'Girls'), (b'3', 'Mixed')])), ('ownership', models.CharField(default=b'1', help_text='Private or public', max_length=1, verbose_name='Ownership', choices=[(b'1', 'Public'), (b'2', 'Private')])), ('sponsor', models.CharField(default=b'1', max_length=1, verbose_name='School Sponsor', choices=[(b'1', 'Central Government/DEB'), (b'2', 'Religious Organisation'), (b'3', 'Community'), (b'4', 'NGO/CBO'), (b'5', 'Private Individual')])), ('student_needs', models.CharField(default=b'1', help_text='Ordinary, Special or Integrated', max_length=1, verbose_name='Student Needs', choices=[(b'1', 'Ordnirary'), (b'2', 'Special'), (b'3', 'Integrated')])), ('is_active', models.BooleanField(default=True, help_text='Designates whether this school is active.', verbose_name='Active')), ('coordinates', django.contrib.gis.db.models.fields.PointField(help_text='Represented as (longitude, latitude)', srid=4326, verbose_name='Coordinates')), ('constituency', models.ForeignKey(verbose_name='Constituency', to='places.Constituency')), ('county', models.ForeignKey(verbose_name='County', to='places.County')), ('district', models.ForeignKey(default=None, blank=True, to='places.District', null=True, verbose_name='District')), ('division', models.ForeignKey(default=None, blank=True, to='places.Division', null=True, verbose_name='Division')), ('location', models.ForeignKey(default=None, blank=True, to='places.Location', null=True, verbose_name='Location')), ('province', models.ForeignKey(default=None, blank=True, to='places.Province', null=True, verbose_name='Province')), ('school_sone', models.ForeignKey(default=None, blank=True, to='places.SchoolZone', null=True, verbose_name='School Zone')), ('sub_location', models.ForeignKey(default=None, blank=True, to='places.SubLocation', null=True, verbose_name='Sub Location')), ], options={ }, bases=(models.Model,), ), ]

[ "kelvin@jayanoris.com" ]

kelvin@jayanoris.com

c5ccb7cfc36c468958d0fc2b2ea1064cf718c1ff

857a9e588a04b40a66b6ca115063cb67ef0427ea

/tests/divine/test_divine.py

4eb4b8f22e7a7f5b61a5e6b996c19c894ba6ebaa

[ "MIT" ]

permissive

rambam613/timemachines

81b88357498871f77efed0faf9c25b4c408d822c

cd243d4606b4ad9c1d419988fc6c04b0964af2e6

refs/heads/main

2023-07-03T07:06:24.421114

2021-08-07T17:42:40

393,793,785

1

0

MIT

2021-08-07T21:13:35

2021-08-07T21:13:34

null

UTF-8

Python

false

548

py

from timemachines.skaters.divine.divineinclusion import using_divinity, dv if using_divinity: from timemachines.skaters.divine.divineskaters import divine_univariate from timemachines.skatertools.evaluation.evaluators import hospital_mean_square_error_with_sporadic_fit def dont_test_divine(): # too noisy err = hospital_mean_square_error_with_sporadic_fit(f=divine_univariate, n=105) # Won't get past warmup so not a real test if __name__=='__main__': assert using_divinity,'pip install divinity' dont_test_divine()

[ "peter.cotton@microprediction.com" ]

peter.cotton@microprediction.com

802ad3fb02a6b071dcd0ec62f89c642999da7259

812f9822ddbfc986f4f230a9e6814f22c7c50e2f

/looping/perfect_generation.py

a86f8a3a5f67f02a0940915cb68d7f44d3a29483

[]

no_license

devopsvj/PythonAndMe

31b4aa9bade1431d6f13917122dc12bf6a118da6

0b1362023960b7c77c79856d4bdef0a58fec1446

refs/heads/master

2023-07-25T23:06:39.081191

2019-01-15T09:50:08

null

0

null

UTF-8

Python

false

247

py

print "Perfect Number Generation " print "--------------------------" n=input("Range to generate : ") j=1 while j<=n: i=1 ans=0 while i<j: if j%i==0: ans=ans+i i=i+1 if ans==j: print j j=j+1

[ "vani_kani@hotmail.com" ]

vani_kani@hotmail.com

0f37657bada84d6c01e51ab37c33ece7d932747d

d4aff784639249a076fe43812e73a6018bb92470

/backend/radio_sagun_18170/settings.py

1e852819826f7c17120fdaeedd60bd9b52d09a5c

[]

no_license

crowdbotics-apps/radio-sagun-18170

9b8d5905886eee6d6639e00b01a1ee1c4bcfce51

2c841cf71152663db6e1cb57aa9f11eaf37fa201

refs/heads/master

2022-10-28T10:20:21.208094

2020-06-17T21:56:05

273,085,286

0

null

UTF-8

Python

false

5,748

py

""" Django settings for radio_sagun_18170 project. Generated by 'django-admin startproject' using Django 2.2.2. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os import environ env = environ.Env() # SECURITY WARNING: don't run with debug turned on in production! DEBUG = env.bool("DEBUG", default=False) # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = env.str("SECRET_KEY") ALLOWED_HOSTS = env.list("HOST", default=["*"]) SITE_ID = 1 SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") SECURE_SSL_REDIRECT = env.bool("SECURE_REDIRECT", default=False) # Application definition INSTALLED_APPS = [ "django.contrib.admin", "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.staticfiles", "django.contrib.sites", "event", ] LOCAL_APPS = [ "home", "users.apps.UsersConfig", ] THIRD_PARTY_APPS = [ "rest_framework", "rest_framework.authtoken", "rest_auth", "rest_auth.registration", "bootstrap4", "allauth", "allauth.account", "allauth.socialaccount", "allauth.socialaccount.providers.google", "django_extensions", "drf_yasg", # start fcm_django push notifications "fcm_django", # end fcm_django push notifications ] INSTALLED_APPS += LOCAL_APPS + THIRD_PARTY_APPS MIDDLEWARE = [ "django.middleware.security.SecurityMiddleware", "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.common.CommonMiddleware", "django.middleware.csrf.CsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "django.middleware.clickjacking.XFrameOptionsMiddleware", ] ROOT_URLCONF = "radio_sagun_18170.urls" TEMPLATES = [ { "BACKEND": "django.template.backends.django.DjangoTemplates", "DIRS": [], "APP_DIRS": True, "OPTIONS": { "context_processors": [ "django.template.context_processors.debug", "django.template.context_processors.request", "django.contrib.auth.context_processors.auth", "django.contrib.messages.context_processors.messages", ], }, }, ] WSGI_APPLICATION = "radio_sagun_18170.wsgi.application" # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { "default": { "ENGINE": "django.db.backends.sqlite3", "NAME": os.path.join(BASE_DIR, "db.sqlite3"), } } if env.str("DATABASE_URL", default=None): DATABASES = {"default": env.db()} # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { "NAME": "django.contrib.auth.password_validation.UserAttributeSimilarityValidator", }, {"NAME": "django.contrib.auth.password_validation.MinimumLengthValidator",}, {"NAME": "django.contrib.auth.password_validation.CommonPasswordValidator",}, {"NAME": "django.contrib.auth.password_validation.NumericPasswordValidator",}, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = "en-us" TIME_ZONE = "UTC" USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = "/static/" MIDDLEWARE += ["whitenoise.middleware.WhiteNoiseMiddleware"] AUTHENTICATION_BACKENDS = ( "django.contrib.auth.backends.ModelBackend", "allauth.account.auth_backends.AuthenticationBackend", ) STATIC_ROOT = os.path.join(BASE_DIR, "staticfiles") STATICFILES_DIRS = [os.path.join(BASE_DIR, "static")] STATICFILES_STORAGE = "whitenoise.storage.CompressedManifestStaticFilesStorage" # allauth / users ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_AUTHENTICATION_METHOD = "email" ACCOUNT_USERNAME_REQUIRED = False ACCOUNT_EMAIL_VERIFICATION = "mandatory" ACCOUNT_CONFIRM_EMAIL_ON_GET = True ACCOUNT_LOGIN_ON_EMAIL_CONFIRMATION = True ACCOUNT_UNIQUE_EMAIL = True LOGIN_REDIRECT_URL = "users:redirect" ACCOUNT_ADAPTER = "users.adapters.AccountAdapter" SOCIALACCOUNT_ADAPTER = "users.adapters.SocialAccountAdapter" ACCOUNT_ALLOW_REGISTRATION = env.bool("ACCOUNT_ALLOW_REGISTRATION", True) SOCIALACCOUNT_ALLOW_REGISTRATION = env.bool("SOCIALACCOUNT_ALLOW_REGISTRATION", True) REST_AUTH_SERIALIZERS = { # Replace password reset serializer to fix 500 error "PASSWORD_RESET_SERIALIZER": "home.api.v1.serializers.PasswordSerializer", } REST_AUTH_REGISTER_SERIALIZERS = { # Use custom serializer that has no username and matches web signup "REGISTER_SERIALIZER": "home.api.v1.serializers.SignupSerializer", } # Custom user model AUTH_USER_MODEL = "users.User" EMAIL_HOST = env.str("EMAIL_HOST", "smtp.sendgrid.net") EMAIL_HOST_USER = env.str("SENDGRID_USERNAME", "") EMAIL_HOST_PASSWORD = env.str("SENDGRID_PASSWORD", "") EMAIL_PORT = 587 EMAIL_USE_TLS = True # start fcm_django push notifications FCM_DJANGO_SETTINGS = {"FCM_SERVER_KEY": env.str("FCM_SERVER_KEY", "")} # end fcm_django push notifications if DEBUG: # output email to console instead of sending EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend"

[ "team@crowdbotics.com" ]

team@crowdbotics.com

464c5cad5d003f680a9d218634ceb614aa5b67e1

375fceebffcf4b6a0d9fd8a8b44a743091ab403b

/scheduler/serializers.py

4fe01a141dfc65b6ddcb71c5ff6aa22431535802

[]

no_license

Nextafari/email-microapi-1

c06e031645fdaa85eac015898db4800a0c83bcd7

bd831853a8512f10a5d78d6f93c7f3b72f951259

refs/heads/develop

2022-12-20T08:44:28.905092

2020-07-24T10:49:13

282,280,619

1

0

null

2020-07-24T17:36:12

2020-07-24T17:36:11

null

UTF-8

Python

false

311

py

from rest_framework import serializers, fields from rest_framework.validators import UniqueValidator class EmailSchedulingSerializer(serializers.Serializer): sender = serializers.EmailField() recipient = serializers.EmailField() subject = serializers.CharField() body = serializers.CharField()

[ "phemmylintry@gmail.com" ]

phemmylintry@gmail.com

eabb11f0ea5d6fdb3b2907edd8e5ee2c6ef9d9fe

5a61ba76c770de8469218ff457213e122e08c7d1

/code/at_offer/finding_sorting/coding_interview53_2.py

55664b811beef5e8d3fc5efff8641a455f31d94b

[ "Apache-2.0" ]

permissive

zhangrong1722/interview

6a71af26f08f036a294e36073cb9eb6ca798b993

187a485de0774561eb843d8ee640236adda97b90

refs/heads/master

2020-09-06T08:15:00.229710

2019-12-10T06:32:05

220,372,777

2

1

null

UTF-8

Python

false

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""" 题目：0~n-1中缺失的数字一个长度为n-1的递增排序数组中的所有数字都是唯一的并且每个数字都在范围0~n-1之内在范围0~n-1内的n个数字中有且只有一个数字不在该数组中请找出这个数字思路：最直观的方法是直接扫描整个数组此时时间复杂度为O(n) 但是这样显然没有用好递增排序数组这一条件对于递增排序数组条件首先想到的就是二分法查找假设该数字所在位置为m 则在m位置之前所有元素值和元素下标是相等的换句话说这道题就转化为查找第一个元素值和下标不等的元素 """ class Solution(object): def FindMissingNum(self, data): if data is None or len(data) == 0: return -1 left, right, middle = 0, len(data) - 1, 0 while left <= right: middle = (left + right) // 2 if data[middle] != middle: if middle == 0 or (middle - 1 >= 0 and data[middle - 1] == middle - 1): break right = middle - 1 else: left = middle + 1 if middle == len(data) - 1: return -1 else: return data[middle] - 1 s = Solution() print(s.FindMissingNum([0, 1, 2, 3]))

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#! /usr/bin/env python3 # -*- coding: utf-8 -*- # # michael a.g. aïvázis <michael.aivazis@para-sim.com> # (c) 1998-2020 all rights reserved def test(): """ Verify the channel initial state """ # get the journal import journal # make a channel channel = journal.warning(name="tests.journal.warning") # verify the channel name assert channel.name == "tests.journal.warning" # the verbosity should be at the default level assert channel.verbosity == 1 # the channel should be active assert channel.active == True # and non fatal assert channel.fatal == False # the page should be empty assert list(channel.page) == [] # verify the metadata assert channel.notes["application"] == "journal" assert channel.notes["channel"] == channel.name assert channel.notes["severity"] == channel.severity # all done return # main if __name__ == "__main__": # run the test test() # end of file

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"""Abstract Crossover class """ # module imports from ..Operator import KindOperator, Operator # main mutation class class Crossover(Operator): """Abstract crossover extend from Operator Attributes: kind: {KindOperator} -- specify the kind of operator """ def __init__(self): self.kind = KindOperator.CROSSOVER def apply(self, solution): raise NotImplementedError

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import numpy as np import sys import math import time import csv from hpolib.benchmarks.synthetic_functions import Rosenbrock from time import gmtime, strftime def main(job_id, params): print '!!! Entered Main !!!' print 'Anything printed here will end up in the output directory for job #:', str(job_id) print params f = Rosenbrock() res = f.objective_function([params['x'], params['y']]) print res with open('/home/mansurm/Experiments/rosenbrock/run11.csv','a') as csvfile: writer = csv.writer(csvfile, delimiter=',') writer.writerow([res['main'][0]]) return res['main'][0]

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from artemis.fileman.smart_io import smart_load from artemis.general.should_be_builtins import bad_value from artemis.plotting.db_plotting import dbplot from plato.tools.pretrained_networks.vggnet import get_vgg_net, im2vgginput, get_vgg_label_at import numpy as np import time __author__ = 'peter' import os """ This program scans for photos from the webcam, then processes them with vggnet. It looks for photos in the directory that the "Photo Booth" application on MacOS puts photos from the webcam. The first time processing the image should take ~20s, each time after that ~1s. To Use (only works on Mac) - Open PhotoBooth. - Take a screenshot - A window should pop up showing the image with the label that the network decides on - Repeat """ def get_photo_dir(): return os.path.join(os.path.expanduser('~'), 'Pictures/Photo Booth Library/Pictures') def get_all_photos(): return os.listdir(get_photo_dir()) def get_latest_screenshot(): photodir = get_photo_dir() files = os.listdir(photodir) latest = sorted(files)[-1] full_path = os.path.join(photodir, latest) return full_path def classify(f, im_path): im = smart_load(im_path) print 'Processing image... "%s"' % (im_path, ) inputs = im2vgginput(im) out = f(inputs) amax = np.argmax(out[0]) label = get_vgg_label_at(amax) print 'Done.' dbplot(np.rollaxis(inputs[0], 0, 3)[..., ::-1], 'Photo', title="{label}: {pct}%".format(label = label, pct = out[0, amax, 0, 0]*100)) def demo_photobooth(): old_photos = set(get_all_photos()) f = get_vgg_net().compile(add_test_values = False) print 'Take a screenshot with PhotoBooth' while True: new_photos = set(get_all_photos()).difference(old_photos) if len(new_photos) != 0: classify(f, os.path.join(get_photo_dir(), new_photos.pop())) old_photos = set(get_all_photos()) time.sleep(.1) def demo_file_path(): f = get_vgg_net().compile(add_test_values = False) while True: im_path = raw_input("Enter Image Path: ") classify(f, im_path) if __name__ == '__main__': VERSION = "photobooth" if VERSION == 'photobooth': demo_photobooth() elif VERSION == 'file': demo_file_path() else: bad_value(VERSION)

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from ctypes import * from ctypes.wintypes import * LPBYTE = POINTER(BYTE) class STARTUPINFOW(Structure): _fields_ = [ ('cb', DWORD), ('lpReserved', LPWSTR), ('lpDesktop', LPWSTR), ("dwX", DWORD), ("dwY", DWORD), ("dwXSize", DWORD), ("dwYSize", DWORD), ("dwXCountChars", DWORD), ("dwYCountChars", DWORD), ("dwFillAtrribute", DWORD), ("dwFlags", DWORD), ("wShowWindow", WORD), ("cbReserved2", WORD), ("lpReserved2", LPBYTE), ("hStdInput", HANDLE), ("hStdOutput", HANDLE), ("hStdError", HANDLE), ] class PROCESS_INFORMATION(Structure): _fields_ = [ ("hProcess", HANDLE), ("hThread", HANDLE), ("dwProcessId", DWORD), ("dwThreadId", DWORD), ] CreateProcessW = windll.kernel32.CreateProcessW startupinfow = STARTUPINFOW() process_information = PROCESS_INFORMATION() def systemw(cmd): if not isinstance(cmd, unicode): cmd = cmd.decode('mbcs') return CreateProcessW( None, cmd, None, None, 0, None, None, None, byref(startupinfow), byref(process_information), ) if __name__ == '__main__': systemw('calc')

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import sys sys.path.insert(1,"../../../") import h2o from tests import pyunit_utils from h2o.estimators.glrm import H2OGeneralizedLowRankEstimator from h2o.estimators.pca import H2OPrincipalComponentAnalysisEstimator as H2OPCA # This unit test makes sure that GLRM will not return proportional of variance with values exceeding 1 when # categorical columns exist. However, when there are categorical columns, if the sole purpose is to perform # PCA, I will not recommend using GLRM. The reason is due to GLRM will optimize the categorical columns # using a categorical loss and not the quadratic loss as in PCA algos. The eigenvalues obtained from PCA # and GLRM differs in this case. def glrm_iris(): print("Importing iris.csv data...") irisH2O = h2o.upload_file(pyunit_utils.locate("smalldata/iris/iris.csv")) irisH2O.describe() print("@@@@@@ Building PCA with GramSVD...\n") glrmPCA = H2OPCA(k=5, transform="STANDARDIZE", pca_method="GLRM", use_all_factor_levels=True, seed=21) glrmPCA.train(x=irisH2O.names, training_frame=irisH2O) glrm_h2o = H2OGeneralizedLowRankEstimator(k=5, loss="Quadratic",transform="STANDARDIZE", recover_svd=True, seed=21) glrm_h2o.train(x=irisH2O.names, training_frame=irisH2O) # compare singular values and stuff with GramSVD print("@@@@@@ Comparing eigenvalues between GramSVD and GLRM...\n") pyunit_utils.assert_H2OTwoDimTable_equal(glrmPCA._model_json["output"]["importance"], glrm_h2o._model_json["output"]["importance"], ["Standard deviation", "Cumulative Proportion", "Cumulative Proportion"], tolerance=1e-6) print("@@@@@@ Comparing eigenvectors between GramSVD and GLRM...\n") # compare singular vectors pyunit_utils.assert_H2OTwoDimTable_equal(glrmPCA._model_json["output"]["eigenvectors"], glrm_h2o._model_json["output"]["eigenvectors"], glrm_h2o._model_json["output"]["names"], tolerance=1e-6,check_sign=True) # check to make sure maximum proportional variance <= 1 assert glrmPCA._model_json["output"]["importance"].cell_values[1][1] <= 1, \ "Expected value <= 1.0 but received {0}".format(glrmPCA._model_json["output"]["importance"].cell_values[1][1]) if __name__ == "__main__": pyunit_utils.standalone_test(glrm_iris) else: glrm_iris()

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from flask import Flask app = Flask(__name__) @app.route('/') def index(): return '<h1>Hello Puppy!</h1>' if __name__ == '__main__': app.run()

[ "sndp1811@gmail.com" ]

sndp1811@gmail.com

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/server/src/uds/reports/stats/pools_usage_day.py

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git38438/openuds

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# -*- coding: utf-8 -*- # # Copyright (c) 2015 Virtual Cable S.L. # All rights reserved. # # Redistribution and use in source and binary forms, with or without modification, # are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # * Neither the name of Virtual Cable S.L. nor the names of its contributors # may be used to endorse or promote products derived from this software # without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. """ .. moduleauthor:: Adolfo Gómez, dkmaster at dkmon dot com """ from django.utils.translation import ugettext, ugettext_lazy as _ from uds.core.ui.UserInterface import gui from uds.core.util.stats import counters import csv import io import datetime import logging from .base import StatsReport from uds.models import ServicePool from uds.core.reports import graphs logger = logging.getLogger(__name__) __updated__ = '2018-04-25' # several constants as Width height, margins, .. WIDTH, HEIGHT, DPI = 19.2, 10.8, 100 SIZE = (WIDTH, HEIGHT, DPI) class CountersPoolAssigned(StatsReport): filename = 'pools_counters.pdf' name = _('Pools usage on a day') # Report name description = _('Pools usage counters for an specific day') # Report description uuid = '0b429f70-2fc6-11e7-9a2a-8fc37101e66a' startDate = gui.DateField( order=2, label=_('Date'), tooltip=_('Date for report'), defvalue='', required=True ) pools = gui.MultiChoiceField( order=1, label=_('Pools'), tooltip=_('Pools for report'), required=True ) def initialize(self, values): pass def initGui(self): logger.debug('Initializing gui') vals = [ gui.choiceItem(v.uuid, v.name) for v in ServicePool.objects.all().order_by('name') ] self.pools.setValues(vals) def getData(self): # Generate the sampling intervals and get dataUsers from db start = self.startDate.date() end = self.startDate.date() + datetime.timedelta(days=1) data = [] pool = None for poolUuid in self.pools.value: try: pool = ServicePool.objects.get(uuid=poolUuid) except Exception: pass # Ignore pool hours = {} for i in range(24): hours[i] = i * i for x in counters.getCounters(pool, counters.CT_ASSIGNED, since=start, to=end, limit=24, use_max=True, all=False): hour = x[0].hour val = int(x[1]) if hours[hour] < val: hours[hour] = val data.append({'uuid':pool.uuid, 'name': pool.name, 'hours': hours}) logger.debug('data: {}'.format(data)) return data def generate(self): items = self.getData() graph1 = io.BytesIO() X = list(range(24)) d = { 'title': _('Services by hour'), 'x': X, 'xtickFnc': lambda l: '{:02d}'.format(l), 'xlabel': _('Hour'), 'y': [ { 'label': i['name'], 'data': [i['hours'][v] for v in X] } for i in items ], 'ylabel': 'Services' } graphs.barChart(SIZE, d, graph1) return self.templateAsPDF( 'uds/reports/stats/pools-usage-day.html', dct={ 'data': items, 'pools': [v.name for v in ServicePool.objects.filter(uuid__in=self.pools.value)], 'beginning': self.startDate.date(), }, header=ugettext('Services usage report for a day'), water=ugettext('Service usage report'), images={'graph1': graph1.getvalue()}, ) class CountersPoolAssignedCSV(CountersPoolAssigned): filename = 'pools_counters.csv' mime_type = 'text/csv' # Report returns pdfs by default, but could be anything else uuid = '1491148a-2fc6-11e7-a5ad-03d9a417561c' encoded = False # Input fields startDate = CountersPoolAssigned.startDate pools = CountersPoolAssigned.pools def generate(self): output = io.StringIO() writer = csv.writer(output) writer.writerow([ugettext('Pool'), ugettext('Hour'), ugettext('Services')]) items = self.getData() for i in items: for j in range(24): writer.writerow([i['name'], '{:02d}'.format(j), i['hours'][j]]) return output.getvalue()

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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2020/4/3 18:05 # @Author : lihanhan # @Email : demo1li@163.com # @File : __init__.py.py

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""" Finish the solution so that it takes an input 'n' (integer) and returns a string that is the decimal representation of the number grouped by commas after every 3 digits. Assume: 0 <= n < 1000000000 1 -> "1" 10 -> "10" 100 -> "100" 1000 -> "1,000" 10000 -> "10,000" 100000 -> "100,000" 1000000 -> "1,000,000" 35235235 -> "35,235,235" """ def group_by_commas(string): rev = string[::-1] if len(rev) <= 3: return rev[::-1] else: return group_by_commas(rev[3:][::-1]) + "," + rev[:3][::-1] print group_by_commas("1") print group_by_commas("10") print group_by_commas("100") print group_by_commas("1000") print group_by_commas("10000") print group_by_commas("100000") print group_by_commas("1000000") print group_by_commas("35235235")

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# coding: utf-8 """ Sage Business Cloud Accounting - Accounts Documentation of the Sage Business Cloud Accounting API. # noqa: E501 The version of the OpenAPI document: 3.1 Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six from openapi_client.configuration import Configuration class PutSalesQuotes(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_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. """ openapi_types = { 'sales_quote': 'PutSalesQuotesSalesQuote' } attribute_map = { 'sales_quote': 'sales_quote' } def __init__(self, sales_quote=None, local_vars_configuration=None): # noqa: E501 """PutSalesQuotes - a model defined in OpenAPI""" # noqa: E501 if local_vars_configuration is None: local_vars_configuration = Configuration() self.local_vars_configuration = local_vars_configuration self._sales_quote = None self.discriminator = None if sales_quote is not None: self.sales_quote = sales_quote @property def sales_quote(self): """Gets the sales_quote of this PutSalesQuotes. # noqa: E501 :return: The sales_quote of this PutSalesQuotes. # noqa: E501 :rtype: PutSalesQuotesSalesQuote """ return self._sales_quote @sales_quote.setter def sales_quote(self, sales_quote): """Sets the sales_quote of this PutSalesQuotes. :param sales_quote: The sales_quote of this PutSalesQuotes. # noqa: E501 :type: PutSalesQuotesSalesQuote """ self._sales_quote = sales_quote def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_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, PutSalesQuotes): return False return self.to_dict() == other.to_dict() def __ne__(self, other): """Returns true if both objects are not equal""" if not isinstance(other, PutSalesQuotes): return True return self.to_dict() != other.to_dict()

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kevin.gray@eurekasolutions.co.uk

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/expense_tracker/views/default.py

a4fe3759abf52803017cfbc6dfc29d4947a4c575

[ "MIT" ]

permissive

jjskim/expense_tracker_401d7

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284d57829117e05aed700346c75e77b76fa25480

refs/heads/master

2021-07-22T05:37:57.603103

2017-10-31T19:09:16

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from pyramid.view import view_config from datetime import datetime from pyramid.httpexceptions import HTTPNotFound FMT = '%m/%d/%Y' EXPENSES = [ {'id': 1, 'title': 'Rent', 'amount': 50000, 'due_date': datetime.strptime('11/1/2017', FMT)}, {'id': 2, 'title': 'Phone Bill', 'amount': 100, 'due_date': datetime.strptime('11/27/2017', FMT)}, {'id': 3, 'title': 'Food', 'amount': 600, 'due_date': datetime.strptime('11/2/2017', FMT)}, {'id': 4, 'title': 'Car', 'amount': 270, 'due_date': datetime.strptime('11/25/2017', FMT)}, {'id': 5, 'title': 'Internet', 'amount': 100, 'due_date': datetime.strptime('11/12/2017', FMT)}, ] @view_config(route_name='home', renderer="expense_tracker:templates/index.jinja2") def list_expenses(request): return { "title": "Expense List", "expenses": EXPENSES } @view_config(route_name='detail', renderer="expense_tracker:templates/detail.jinja2") def expense_detail(request): expense_id = int(request.matchdict['id']) if expense_id < 0 or expense_id > len(EXPENSES) - 1: raise HTTPNotFound expense = list(filter(lambda expense: expense['id'] == expense_id, EXPENSES))[0] return { 'title': 'One Expense', 'expense': expense } @view_config(route_name="api_detail", renderer="json") def api_detail(request): expense_id = int(request.matchdict['id']) if expense_id < 0 or expense_id > len(EXPENSES) - 1: raise HTTPNotFound expense = list(filter(lambda expense: expense['id'] == expense_id, EXPENSES))[0] expense['due_date'] = expense['due_date'].strftime(FMT) return { 'title': 'One Expense', 'expense': expense }

[ "nhuntwalker@gmail.com" ]

nhuntwalker@gmail.com