def __new__(cls, end_date):
min_datetime = pendulum.from_format(settings.FOUNDATION_DATE,
settings.FILE_DATE_FORMAT)
max_datetime = pendulum.today()
try:
end_date = pendulum.from_format(end_date,
settings.FILE_DATE_FORMAT).date()
except (ValueError, TypeError):
raise exceptions.ArgumentTypeError(settings.END_DATE_ERROR)
else:
if min_datetime.date() <= end_date <= max_datetime.date():
return super().__new__(cls, end_date.year, end_date.month,
end_date.day)
else:
raise exceptions.ArgumentTypeError(settings.END_DATE_ERROR)
def __new__(cls, cpu_count):
if not cpu_count:
cpu_count = mp.cpu_count()
return super().__new__(cls, cpu_count)
elif cpu_count in list(range(1, mp.cpu_count() + 1)):
return super().__new__(cls, cpu_count)
else:
raise exceptions.ArgumentTypeError(settings.CPU_COUNT_ERROR)
def __new__(cls, directory_path):
if not directory_path:
directory_path = pathlib.Path.cwd()
return super().__new__(cls, directory_path)
try:
directory_path = pathlib.Path(directory_path)
except TypeError:
raise exceptions.ArgumentTypeError(settings.DIRECTORY_PATH_ERROR)
else:
return super().__new__(cls, directory_path)
def __init__(self, name, region_names):
regions = sc.download_regions(name)
if set(region_names).issubset(regions.keys()):
super().__init__(sorted(set(region_names)))
else:
raise exceptions.ArgumentTypeError(settings.REGION_NAME_ERROR)
def __new__(cls, periodicity):
if periodicity in settings.PERIODICITY_CODES:
return super().__new__(cls, periodicity)
else:
raise exceptions.ArgumentTypeError(settings.PERIODICITY_ERROR)
def __new__(cls, name):
if name in settings.NAME_CODES:
return super().__new__(cls, name)
else:
raise exceptions.ArgumentTypeError(settings.NAME_ERROR)
def __init__(self,
name,
periodicity,
region_names,
begin_date,
end_date,
cpu_count=None,
directory_path=None):
self._name = classes.Name(name)
self._periodicity = classes.Periodicity(periodicity)
self._region_names = classes.RegionNames(name, region_names)
self._begin_date = classes.BeginDate(begin_date)
self._end_date = classes.EndDate(end_date)
if self._begin_date > self._end_date:
raise exceptions.ArgumentTypeError(settings.DATE_RANGE_ERROR)
self._cpu_count = classes.CpuCount(cpu_count)
self._directory_path = classes.DirectoryPath(directory_path)
name_code = settings.NAME_CODES[self.name]
periodicity_code = settings.PERIODICITY_CODES[self.periodicity]
all_regions = download_regions(self.name)
regions = {}
for region_name in all_regions:
if region_name in self.region_names:
regions[region_name] = all_regions[region_name]
regions_items = sorted(regions.items(), key=lambda region: region[0])
regions_items = auto.tqdm(regions_items)
if self.name == 'top200':
column_names = copy.deepcopy(settings.TOP200_CHART_COLUMN_NAMES)
else:
column_names = copy.deepcopy(settings.VIRAL50_CHART_COLUMN_NAMES)
column_names.extend(['region_name', 'date'])
begin_date = self.begin_date.format(settings.FILE_DATE_FORMAT)
end_date = self.end_date.format(settings.FILE_DATE_FORMAT)
extension = settings.FILE_EXTENSION
for region_name, region_code in regions_items:
file_name = f'{self.name}_{self.periodicity}_charts_from_{begin_date}_to_{end_date}.{extension}'
directory_path = pathlib.Path(self.directory_path).joinpath(
self.name, self.periodicity, region_name)
directory_path.mkdir(parents=True, exist_ok=True)
file_path = directory_path.joinpath(file_name)
if file_path.exists():
region_charts = pd.read_csv(file_path,
sep=settings.FILE_DELIMITER,
encoding=settings.FILE_ENCODING)
else:
region_charts = pd.DataFrame(columns=column_names)
file_dates = []
for file_date in region_charts['date'].unique():
file_date = pendulum.instance(
pd.Timestamp(file_date).to_pydatetime()).date()
file_dates.append(file_date)
current_time = pendulum.now().format(
settings.PROGRESS_BAR_TIME_FORMAT)
description = f'{current_time} | {region_name}'
regions_items.set_description(description)
all_dates = download_dates(self.name, self.periodicity,
region_name)
urls = []
dates = []
for date, date_code in all_dates.items():
if self.begin_date <= date <= self.end_date and date not in file_dates:
url = f'{settings.SPOTIFY_CHARTS_URL}/{name_code}/{region_code}/{periodicity_code}/{date_code}'
urls.append(url)
dates.append(date)
logger.info(f'{region_name}:{len(urls)}')
with mp.Pool(self.cpu_count) as pool:
downloaded_charts = pool.map(classes.Chart, urls)
for chart, date in zip(downloaded_charts, dates):
if not chart.empty:
chart['region_name'] = region_name
chart['date'] = date
chart['date'] = pd.to_datetime(chart['date'])
if downloaded_charts:
data = region_charts.append(downloaded_charts, sort=True)
data.reset_index(drop=True, inplace=True)
data.sort_values(by=['date', 'track_position'],
ascending=[False, True],
inplace=True)
data = data[column_names]
data.to_csv(file_path,
sep=settings.FILE_DELIMITER,
encoding=settings.FILE_ENCODING,
index=False)
regions_items.close()