mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-07 05:33:51 +08:00
Michael Schatzow
59bcd097d5
This creates a data source for csv and hdf5 files, a generator to create a sample csv, and a pytables generator to go from a list of dated gzipped csv's in a directory to a pytables data source. This does not add a unittest yet which we should write for the future.
221 lines
8.2 KiB
Python
221 lines
8.2 KiB
Python
# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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leverage work of briancappello and quantopian team
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(especially twiecki, eddie, and fawce)
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"""
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import pandas as pd
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from zipline.gens.utils import hash_args
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from zipline.sources.data_source import DataSource
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import datetime
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import numpy as np
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import dateutil.parser
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import tables
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def _iterate_ohlc(date_node, sid_filter, sids, start_ts, end_ts):
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last_stamp = None
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last_ts = None
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volumes = {}
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price_volumes = {}
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cols = np.array(["open", "high", "low", "close"])
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for row in date_node.iterrows():
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sid = row["sid"]
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if sid_filter and sid in sid_filter:
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continue
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elif sids is None or sid in sids:
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if sid not in volumes:
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volumes[sid] = 0
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price_volumes[sid] = 0
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if last_stamp and row["dt"] == last_stamp:
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ts = last_ts
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else:
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ts = pd.Timestamp(np.datetime64(row["dt"], "s"), tz='utc')
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last_ts = ts
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last_stamp = row["dt"]
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if (start_ts > ts) or (ts > end_ts):
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continue
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event = {"sid": sid, "type": "TRADE", "symbol": sid}
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event["dt"] = ts
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event["price"] = row["close"]
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event["volume"] = row["volume"]
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volumes[sid] += event["volume"]
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price_volumes[sid] += event["price"] * event["volume"]
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event["vwap"] = price_volumes[sid] / volumes[sid]
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last_ts = ts
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for field in cols:
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event[field] = row[field]
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yield event
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def _iterate_signal(date_node, sids, sid_filter, start_ts, end_ts):
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last_stamp = None
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last_ts = None
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volumes = {}
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price_volumes = {}
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for row in date_node.iterrows():
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sid = row["sid"]
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if sid_filter and sid in sid_filter:
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continue
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elif sids is None or sid in sids:
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if sid not in volumes:
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volumes[sid] = 0
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price_volumes[sid] = 0
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if last_stamp and row["dt"] == last_stamp:
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ts = last_ts
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else:
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ts = pd.Timestamp(np.datetime64(row["dt"], "s"), tz='utc')
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last_ts = ts
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last_stamp = row["dt"]
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if (start_ts > ts) or (ts > end_ts):
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continue
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event = {"sid": sid, "type": "CUSTOM",
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"signal": row["signal"]}
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yield event
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class DataSourceTablesOHLC(DataSource):
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"""
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Yields all events in event_list that match the given sid_filter.
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If no event_list is specified, generates an internal stream of events
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to filter. Returns all events if filter is None.
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Configuration options:
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sids : list of values representing simulated internal sids
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start : start date
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tz_in : timezzone of table
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filter : filter to remove the sids
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start_time: what time trading should start
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end_time: what time trading should end
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"""
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def __init__(self, data, **kwargs):
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assert isinstance(data, tables.file.File)
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self.data = data
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# Unpack config dictionary with default values.
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if 'symbols' in kwargs:
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self.sids = kwargs.get('symbols')
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else:
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self.sids = None
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self.tz_in = kwargs.get('tz_in', "US/Eastern")
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self.source_id = kwargs.get("source_id", None)
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self.sid_filter = kwargs.get("filter", None)
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self.start = pd.Timestamp(np.datetime64(kwargs.get('start')))
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self.start = self.start.tz_localize('utc')
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self.end = pd.Timestamp(np.datetime64(kwargs.get('end')))
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self.end = self.end.tz_localize('utc')
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start_time_str = kwargs.get("start_time", "9:30")
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end_time_str = kwargs.get("end_time", "16:00")
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self.start_time = dateutil.parser.parse(start_time_str).time()
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self.end_time = dateutil.parser.parse(end_time_str).time()
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self._raw_data = None
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self.arg_string = hash_args(data, **kwargs)
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self.root_node = "/" + kwargs.get('root', "TD") + "/"
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@property
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def instance_hash(self):
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return self.arg_string
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def raw_data_gen(self):
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for date_node in self.data.walkNodes(self.root_node):
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if isinstance(date_node, tables.group.Group):
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continue
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date = dateutil.parser.parse(date_node.name.split("_")[1])
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dt64 = np.datetime64(date)
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table_dt = pd.Timestamp(dt64).tz_localize("utc")
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if table_dt < self.start or table_dt > self.end:
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continue
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start_ts = pd.Timestamp(datetime.datetime.combine(table_dt.date(),
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self.start_time),
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tz=self.tz_in)
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start_ts = start_ts.tz_convert("utc")
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end_ts = pd.Timestamp(datetime.datetime.combine(table_dt.date(),
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self.end_time),
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tz=self.tz_in)
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end_ts = end_ts.tz_convert("utc")
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for item in _iterate_ohlc(date_node, self.sids, self.sid_filter,
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start_ts, end_ts):
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yield item
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@property
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def raw_data(self):
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if not self._raw_data:
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self._raw_data = self.raw_data_gen()
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return self._raw_data
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@property
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def mapping(self):
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return {
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'sid': (lambda x: x, 'sid'),
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'dt': (lambda x: x, 'dt'),
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'open': (lambda x: x, 'open'),
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'high': (lambda x: x, 'high'),
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'low': (lambda x: x, 'low'),
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'close': (lambda x: x, 'close'),
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'price': (lambda x: x, 'price'),
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'volume': (lambda x: x, 'volume'),
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'vwap': (lambda x: x, 'vwap')
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}
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class DataSourceTablesSignal(DataSource):
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def __init__(self, data, **kwargs):
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assert isinstance(data, tables.file.File)
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self.h5file = data
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self.sids = kwargs.get('sids', None)
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self.start = kwargs.get('start')
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self.end = kwargs.get('end')
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self.source_id = kwargs.get("source_id", None)
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self.arg_string = hash_args(data, **kwargs)
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self._raw_data = None
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self.root_node = +"/" + kwargs.get('root', "signal") + "/"
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@property
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def instance_hash(self):
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return self.arg_string
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def raw_data_gen(self):
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for date_node in self.data.walkNodes(self.root_node):
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if isinstance(date_node, tables.group.Group):
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continue
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date = dateutil.parser.parse(date_node.name.split("_")[1])
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dt64 = np.datetime64(date)
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table_dt = pd.Timestamp(dt64).tz_localize("utc")
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if table_dt < self.start or table_dt > self.end:
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continue
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start_ts = pd.Timestamp(datetime.datetime.combine(table_dt.date(),
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self.start_time),
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tz=self.tz_in)
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start_ts = start_ts.tz_convert("utc")
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end_ts = pd.Timestamp(datetime.datetime.combine(table_dt.date(),
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self.end_time),
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tz=self.tz_in)
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end_ts = end_ts.tz_convert("utc")
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table = self.data.getNode(date_node)
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for row in _iterate_signal(table, self.sids, self.sid_filter,
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start_ts, end_ts):
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yield row
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@property
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def raw_data(self):
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if not self._raw_data:
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self._raw_data = self.raw_data_gen()
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return self._raw_data
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@property
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def mapping(self):
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return {
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'sid': (lambda x: x, 'symbol'),
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'dt': (lambda x: x, 'dt'),
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'signal': (lambda x: x, 'signal'),
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}
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