def __getitem__(self, item):
if isinstance(item, str):
return CalculatedStream([item])
elif list_of_instance(item, str):
return CalculatedStream(item)
elif list_of_instance(item, datetime) or isinstance(
item, DatetimeIndex):
return self.all(dates=item)
elif isinstance(item, slice):
# do your handling for a slice object:
print(item.start, item.stop, item.step)
def __contains__(self, item):
if isinstance(item, datetime):
return item in self.dates
elif list_of_instance(item, datetime):
return all([item in self.dates])
else:
return item in self.events
def __getitem__(self, item):
from stateful.storage.calculated_stream import CalculatedStream
if (isinstance(item, str) and
("/" in item or "-" in item)) or isinstance(item, datetime):
date = pd.to_datetime(item, utc=True)
return self.get(date, include_date=False, include_id=False)
if list_of_instance(item, datetime):
return list(self.all(item))
elif isinstance(item, str):
assert item in self.controller.keys, f"{item} not valid a stream"
return CalculatedStream(dependencies=[item], parent=self)
elif list_of_instance(item, str):
for name in item:
assert name in self.controller.keys, f"{name} not valid a stream"
return CalculatedStream(dependencies=item, parent=self)
def df(self) -> pd.DataFrame:
if self.empty:
return pd.DataFrame()
index, values = zip(*list(self._tree))
if list_of_instance(values, dict):
return pd.DataFrame(values, index=index)
else:
return pd.DataFrame(columns={self.name: values}, index=index)
def __getitem__(self, item):
if isinstance(self._state, dict):
if isinstance(item, str):
return self._state.get(item, np.NaN)
if list_of_instance(item, str):
return Event(date=self.date,
state={name: self[name]
for name in item})
else:
raise AttributeError(f"{self.value} is not a dictionary")
def __getitem__(self, item):
if isinstance(item, datetime):
i = self.dates[self.dates == item][0]
return {name: self._state[name][i] for name in self._state.keys()}
if list_of_instance(item, str):
return EventFrame(self.dates,
{name: self._state[name]
for name in item})
return self._state[item]
def head(self, n=5) -> pd.DataFrame:
if self.empty:
return pd.DataFrame()
index, values = [], []
iterator = iter(self._tree)
while len(index) < n:
idx, value = next(iterator)
index.append(idx)
values.append(value)
if list_of_instance(values, dict):
return pd.DataFrame(values, index=index)
else:
name = self.name if self.name else "values"
columns = [{name: v} for v in values]
return pd.DataFrame(columns, index=index)
def _stream_conf(self, key):
if list_of_instance(key, str):
key = "_".join(key)
stream_conf = self.configuration.get(key, {})
stream_conf['on_dublicate'] = 'increment'
return stream_conf