def render_template(template, *args, **kwargs): # If the year has already been set (e.g. for error pages) then use that # Otherwise the requested year, otherwise the default year year = kwargs.get('year', request.view_args.get('year', DEFAULT_YEAR)) # If the lang has already been set (e.g. for error pages) then use that # Otherwise the requested lang, otherwise the default lang lang = kwargs.get( 'lang', request.view_args.get('lang', DEFAULT_LANGUAGE.lang_code)) language = get_language(lang) langcode_length = len( lang) + 1 # Probably always 2-character language codes but who knows! # If the template does not exist, then redirect to English version if (lang != '' and lang != 'en' and not (os.path.isfile('templates/%s' % template))): return redirect('/en%s' % (request.full_path[langcode_length:]), code=302) # Although a langauge may be enabled, all templates may not have been translated yet # So check if each language exists and only return languages for templates that do exist supported_languages = SUPPORTED_LANGUAGES.get(year, (DEFAULT_LANGUAGE, )) template_supported_languages = [] for l in supported_languages: langTemplate = 'templates/%s/%s' % (l.lang_code, template[langcode_length:]) if (os.path.isfile(langTemplate)): template_supported_languages.append(l) kwargs.update(supported_languages=template_supported_languages, year=year, lang=lang, language=language, supported_years=SUPPORTED_YEARS) return flask_render_template(template, *args, **kwargs)
def connect_to_kernel(self, kernel_type, filename=''): """Establish a connection with the specified kernel type. .. note:: vim command `:JupyterConnect` Parameters ---------- kernel_type : str Type of kernel, i.e. `python3` with which to connect. filename : str, optional, default='' Specific kernel connection filename, i.e. ``$(jupyter --runtime)/kernel-123.json`` """ self.kernel_client.kernel_info['kernel_type'] = kernel_type self.kernel_client.kernel_info['cfile_user'] = filename self.lang = get_language(kernel_type) # Create thread self.sync.start_thread(target=self.thread_connect_to_kernel) # Launch timers: update echom for sleep_ms in self.vim_client.get_timer_intervals(): vim_cmd = ('let timer = timer_start(' + str(sleep_ms) + ', "jupyter#UpdateEchom")') vim.command(vim_cmd)
def render_template(template, *args, **kwargs): year = request.view_args.get('year', DEFAULT_YEAR) supported_languages = SUPPORTED_YEARS.get(year, (DEFAULT_LANGUAGE)) lang = request.view_args.get('lang') language = get_language(lang) kwargs.update(supported_languages=supported_languages, language=language) return flask_render_template(template, *args, **kwargs)
def parse( ** kwargs ): for _ in receive_transfer_field: ori = _ tr = receive_transfer_field[_] kwargs[tr] = kwargs[_] kwargs.pop( ori ) kwargs['language'] = get_language( kwargs['language'] ) return kwargs
def parse(**kwargs): for _ in receive_transfer_field: ori = _ tr = receive_transfer_field[_] kwargs[tr] = kwargs[_] kwargs.pop(ori) kwargs['language'] = get_language(kwargs['language']) return kwargs
def __init__(self, mode='shore', n=16384): self.mode = mode self.lang = language.get_language() self.build_grid(n) if '/' in mode: self.mixed_heightmap() mode = mode.split("/")[0] else: self.single_heightmap(mode) self.finalize() self.riverperc = riverpercs[mode] * np.mean(self.elevation > 0) self.place_cities(np.random.randint(*city_counts[mode])) self.grow_territory(np.random.randint(*terr_counts[mode])) self.name_places() self.path_cache = {} self.fill_path_cache(self.big_cities)
def __init__(self): self.sync = Sync() self.kernel_client = JupyterMessenger(self.sync) self.vim_client = VimMessenger(self.sync) self.monitor = Monitor(self) self.lang = get_language('')
import pandas as pd import country import language import safety import _pickle as cPickle import get_trip_advisor_static df = pd.read_csv("scraping/destinations.csv") df['country'] = df.apply(lambda row: country.get_country(row['city']), axis=1) df['language'] = df.apply(lambda row: language.get_language(row['country']), axis=1) df['safety'] = df.apply(lambda row: safety.get_safety(row['country']), axis=1) df['trip_advisor_id'] = df.apply( lambda row: get_trip_advisor_static.get_location_id(row['city']), axis=1) df['attractions'] = df.apply(lambda row: get_trip_advisor_static. get_attractions(row['trip_advisor_id']), axis=1) df.drop_duplicates("cities") with open("trip_advisor_data.pkl", "wb") as f: cPickle.dump(list(df['attractions']), f) del df['attractions']