def _get_range(forecast: pd.DataFrame,
start: pd.Timestamp | dt.datetime,
end: pd.Timestamp | dt.datetime) -> pd.DataFrame:
if start is not None:
start = start.astimezone(forecast.index.tz)
if start is None or start < forecast.index[0]:
start = forecast.index[0]
if end is not None:
end = end.astimezone(forecast.index.tz)
if end is None or end > forecast.index[-1]:
end = forecast.index[-1]
return forecast.loc[start:end, :]
def get(self,
start: pd.Timestamp | dt.datetime = dt.datetime.now(tz.utc),
end: pd.Timestamp | dt.datetime = None,
**kwargs) -> pd.DataFrame:
# Calculate the available forecast start and end times
interval = self.interval/3600
timezone = tz.timezone(self._system.location.tz)
if start.tzinfo is None or start.tzinfo.utcoffset(start) is None:
start = tz.utc.localize(start)
start_schedule = start.astimezone(timezone).replace(minute=0, second=0, microsecond=0)
if start_schedule.hour % interval != 0:
start_schedule = start_schedule - dt.timedelta(hours=start_schedule.hour % interval)
if self._database is not None and self._database.exists(start_schedule, subdir=self._id):
forecast = self._database.read(start_schedule, subdir=self._id)
else:
forecast = self._get(start, **kwargs)
if self._database is not None:
# Store the retrieved forecast
self._database.write(forecast, start=start_schedule, subdir=self._id)
return self._get_range(forecast, start, end)
def _get(self,
start: pd.Timestamp | dt.datetime = None,
end: pd.Timestamp | dt.datetime = None,
format: str = '%d.%m.%Y',
**kwargs) -> pd.DataFrame:
if start is None:
start = tz.utc.localize(dt.datetime.utcnow())
start.replace(year=start.year-1, month=1, day=1, hour=0, minute=0, second=0)
elif isinstance(start, str):
start = tz.utc.localize(dt.datetime.strptime(start, format))
if end is None:
end = start + dt.timedelta(days=364)
elif isinstance(end, str):
end = tz.utc.localize(dt.datetime.strptime(end, format))
return self._database.read(start=start, end=end, **kwargs)
def read(self,
start: pd.Timestamp | dt.datetime = None,
end: pd.Timestamp | dt.datetime = None,
resolution: int = None,
file: str = None,
subdir: str = '',
**kwargs) -> pd.DataFrame:
if file is None:
file = self.file
if file is not None:
data = self._read_file(os.path.join(self.dir, subdir, file), **kwargs)
else:
data = self._read_file(os.path.join(self.dir, subdir, start.strftime(self.format) + '.csv'), **kwargs)
if end is not None:
date = start
while date <= end:
if self.exists(date, subdir=subdir):
date_str = date.strftime(self.format)
data_file = date_str + '.csv'
data = data.combine_first(self._read_file(os.path.join(self.dir, subdir, data_file), **kwargs))
date += dt.timedelta(hours=self.interval)
if resolution is not None and resolution > 900:
offset = (start - start.replace(hour=0, minute=0, second=0, microsecond=0)).total_seconds() % resolution
data = data.resample(str(int(resolution))+'s', base=offset).sum()
if end is not None:
end += dt.timedelta(seconds=resolution)
if end is not None:
if start > end:
return data.truncate(before=start).head(1)
return data[(data.index >= start) & (data.index <= end)]
return data
def read(self,
start: pd.Timestamp | dt.datetime = None,
end: pd.Timestamp | dt.datetime = None,
resolution: int = None,
**kwargs):
epoch = dt.datetime(1970, 1, 1, tzinfo=tz.UTC)
data = pd.DataFrame()
for column, table in self.tables.items():
cursor = self.connector.cursor()
select = "SELECT time, data FROM {0} WHERE ".format(table)
if end is None:
select += "time >= %s ORDER BY time ASC"
cursor.execute(select, ((start.astimezone(tz.UTC)-epoch).total_seconds(),))
else:
select += "time BETWEEN %s AND %s ORDER BY time ASC"
cursor.execute(select,
((start.astimezone(tz.UTC)-epoch).total_seconds(),
(end.astimezone(tz.UTC)-epoch).total_seconds()))
times = []
values = []
for timestamp, value in cursor.fetchall():
time = tz.utc.localize(dt.datetime.fromtimestamp(timestamp))
times.append(time)
values.append(value)
result = pd.DataFrame(data=values, index=times, columns=[column])
data = pd.concat([data, result], axis=1)
if resolution is not None and resolution > 900:
offset = (start - start.replace(hour=0, minute=0, second=0, microsecond=0)).total_seconds() % resolution
data = data.resample(str(int(resolution))+'s', base=offset).sum()
return data
def write(self,
data: pd.DataFrame,
start: pd.Timestamp | dt.datetime = None,
end: pd.Timestamp | dt.datetime = None,
file: str = None,
subdir: str = '',
**kwargs) -> None:
if data is not None and self.enabled:
if start is None:
start = data.index[0]
if end is None:
end = data.index[-1]
if file is None:
file = self.file
if file is None:
file = start.strftime(self.format) + '.csv'
path = os.path.join(self.dir, subdir)
if not os.path.exists(path):
os.makedirs(path)
self._write_file(os.path.join(path, file), data.loc[start:end], **kwargs)
