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