mirror of
https://github.com/wassname/catalyst.git
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twiecki
211 lines
7.2 KiB
Python
211 lines
7.2 KiB
Python
#
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# Copyright 2014 Quantopian, Inc.
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#
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# 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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import sys
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import getopt
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import traceback
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import numpy as np
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import pandas as pd
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import datetime
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import logging
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import tables
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import gzip
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import glob
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import os
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import random
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import csv
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import time
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from six import print_
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FORMAT = "%(asctime)-15s -8s %(message)s"
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logging.basicConfig(format=FORMAT, level=logging.INFO)
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class Usage(Exception):
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def __init__(self, msg):
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self.msg = msg
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OHLCTableDescription = {'sid': tables.StringCol(14, pos=2),
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'dt': tables.Int64Col(pos=1),
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'open': tables.Float64Col(dflt=np.NaN, pos=3),
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'high': tables.Float64Col(dflt=np.NaN, pos=4),
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'low': tables.Float64Col(dflt=np.NaN, pos=5),
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'close': tables.Float64Col(dflt=np.NaN, pos=6),
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"volume": tables.Int64Col(dflt=0, pos=7)}
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def process_line(line):
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dt = np.datetime64(line["dt"]).astype(np.int64)
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sid = line["sid"]
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open_p = float(line["open"])
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high_p = float(line["high"])
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low_p = float(line["low"])
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close_p = float(line["close"])
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volume = int(line["volume"])
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return (dt, sid, open_p, high_p, low_p, close_p, volume)
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def parse_csv(csv_reader):
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previous_date = None
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data = []
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dtype = [('dt', 'int64'), ('sid', '|S14'), ('open', float),
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('high', float), ('low', float), ('close', float),
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('volume', int)]
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for line in csv_reader:
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row = process_line(line)
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current_date = line["dt"][:10].replace("-", "")
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if previous_date and previous_date != current_date:
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rows = np.array(data, dtype=dtype).view(np.recarray)
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yield current_date, rows
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data = []
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data.append(row)
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previous_date = current_date
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def merge_all_files_into_pytables(file_dir, file_out):
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"""
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process each file into pytables
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"""
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start = None
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start = datetime.datetime.now()
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out_h5 = tables.openFile(file_out,
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mode="w",
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title="bars",
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filters=tables.Filters(complevel=9,
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complib='zlib'))
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table = None
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for file_in in glob.glob(file_dir + "/*.gz"):
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gzip_file = gzip.open(file_in)
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expected_header = ["dt", "sid", "open", "high", "low", "close",
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"volume"]
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csv_reader = csv.DictReader(gzip_file)
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header = csv_reader.fieldnames
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if header != expected_header:
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logging.warn("expected header %s\n" % (expected_header))
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logging.warn("header_found %s" % (header))
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return
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for current_date, rows in parse_csv(csv_reader):
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table = out_h5.createTable("/TD", "date_" + current_date,
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OHLCTableDescription,
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expectedrows=len(rows),
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createparents=True)
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table.append(rows)
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table.flush()
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if table is not None:
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table.flush()
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end = datetime.datetime.now()
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diff = (end - start).seconds
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logging.debug("finished it took %d." % (diff))
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def create_fake_csv(file_in):
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fields = ["dt", "sid", "open", "high", "low", "close", "volume"]
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gzip_file = gzip.open(file_in, "w")
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dict_writer = csv.DictWriter(gzip_file, fieldnames=fields)
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current_dt = datetime.date.today() - datetime.timedelta(days=2)
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current_dt = pd.Timestamp(current_dt).replace(hour=9)
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current_dt = current_dt.replace(minute=30)
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end_time = pd.Timestamp(datetime.date.today())
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end_time = end_time.replace(hour=16)
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last_price = 10.0
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while current_dt < end_time:
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row = {}
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row["dt"] = current_dt
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row["sid"] = "test"
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last_price += random.randint(-20, 100) / 10000.0
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row["close"] = last_price
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row["open"] = last_price - 0.01
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row["low"] = last_price - 0.02
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row["high"] = last_price + 0.02
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row["volume"] = random.randint(10, 1000) * 10
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dict_writer.writerow(row)
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current_dt += datetime.timedelta(minutes=1)
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if current_dt.hour > 16:
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current_dt += datetime.timedelta(days=1)
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current_dt = current_dt.replace(hour=9)
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current_dt = current_dt.replace(minute=30)
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gzip_file.close()
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def main(argv=None):
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"""
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This script cleans minute bars into pytables file
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data_source_tables_gen.py
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[--tz_in] sets time zone of data only reasonably fast way to use
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time.tzset()
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[--dir_in] iterates through directory provided of csv files in gzip form
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in form:
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dt, sid, open, high, low, close, volume
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2012-01-01T12:30:30,1234HT,1, 2,3,4.0
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[--fake_csv] creates a fake sample csv to iterate through
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[--file_out] determines output file
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"""
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if argv is None:
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argv = sys.argv
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try:
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dir_in = None
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file_out = "./all.h5"
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fake_csv = None
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try:
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opts, args = getopt.getopt(argv[1:], "hdft",
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["help",
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"dir_in=",
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"debug",
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"tz_in=",
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"fake_csv=",
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"file_out="])
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except getopt.error as msg:
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raise Usage(msg)
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for opt, value in opts:
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if opt in ("--help", "-h"):
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print_(main.__doc__)
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if opt in ("-d", "--debug"):
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logging.basicConfig(format=FORMAT,
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level=logging.DEBUG)
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if opt in ("-d", "--dir_in"):
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dir_in = value
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if opt in ("-o", "--file_out"):
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file_out = value
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if opt in ("--fake_csv"):
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fake_csv = value
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if opt in ("--tz_in"):
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os.environ['TZ'] = value
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time.tzset()
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try:
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if dir_in:
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merge_all_files_into_pytables(dir_in, file_out)
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if fake_csv:
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create_fake_csv(fake_csv)
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except Exception:
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error = "An unhandled error occured in the"
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error += "data_source_tables_gen.py script."
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error += "\n\nTraceback:\n"
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error += '-' * 70 + "\n"
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error += "".join(traceback.format_tb(sys.exc_info()[2]))
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error += repr(sys.exc_info()[1]) + "\n"
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error += str(sys.exc_info()[1]) + "\n"
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error += '-' * 70 + "\n"
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print_(error)
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except Usage as err:
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print_(err.msg)
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print_("for help use --help")
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return 2
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if __name__ == "__main__":
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sys.exit(main())
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