209 lines
8.2 KiB
Python
209 lines
8.2 KiB
Python
import datetime
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import os
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import random
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from typing import Literal, Sequence
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import pytest
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from fincal.core import Frequency, Series
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from fincal.fincal import TimeSeries, create_date_series
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THIS_DIR = os.path.dirname(os.path.abspath(__file__))
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sample_data_path = os.path.join(THIS_DIR, "data")
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def create_test_data(
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frequency: str,
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eomonth: bool,
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n: int,
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gaps: float,
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month_position: Literal["start", "middle", "end"],
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date_as_str: bool,
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as_outer_type: Literal["dict", "list"] = "list",
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as_inner_type: Literal["dict", "list", "tuple"] = "tuple",
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) -> Sequence[tuple]:
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start_dates = {
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"start": datetime.datetime(2016, 1, 1),
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"middle": datetime.datetime(2016, 1, 15),
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"end": datetime.datetime(2016, 1, 31),
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}
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end_date = datetime.datetime(2021, 12, 31)
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dates = create_date_series(start_dates[month_position], end_date, frequency=frequency, eomonth=eomonth)
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dates = dates[:n]
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if gaps:
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num_gaps = int(len(dates) * gaps)
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to_remove = random.sample(dates, num_gaps)
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for i in to_remove:
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dates.remove(i)
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if date_as_str:
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dates = [i.strftime("%Y-%m-%d") for i in dates]
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values = [random.randint(8000, 90000) / 100 for _ in dates]
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data = list(zip(dates, values))
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if as_outer_type == "list":
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if as_inner_type == "list":
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data = [list(i) for i in data]
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elif as_inner_type == "dict[1]":
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data = [dict((i,)) for i in data]
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elif as_inner_type == "dict[2]":
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data = [dict(date=i, value=j) for i, j in data]
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elif as_outer_type == "dict":
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data = dict(data)
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return data
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class TestDateSeries:
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def test_daily(self):
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start_date = datetime.datetime(2020, 1, 1)
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end_date = datetime.datetime(2020, 12, 31)
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d = create_date_series(start_date, end_date, frequency="D")
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assert len(d) == 366
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start_date = datetime.datetime(2017, 1, 1)
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end_date = datetime.datetime(2017, 12, 31)
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d = create_date_series(start_date, end_date, frequency="D")
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assert len(d) == 365
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with pytest.raises(ValueError):
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create_date_series(start_date, end_date, frequency="D", eomonth=True)
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def test_monthly(self):
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start_date = datetime.datetime(2020, 1, 1)
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end_date = datetime.datetime(2020, 12, 31)
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d = create_date_series(start_date, end_date, frequency="M")
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assert len(d) == 12
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d = create_date_series(start_date, end_date, frequency="M", eomonth=True)
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assert datetime.datetime(2020, 2, 29) in d
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start_date = datetime.datetime(2020, 1, 31)
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d = create_date_series(start_date, end_date, frequency="M")
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assert datetime.datetime(2020, 2, 29) in d
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assert datetime.datetime(2020, 8, 31) in d
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assert datetime.datetime(2020, 10, 30) not in d
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start_date = datetime.datetime(2020, 2, 29)
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d = create_date_series(start_date, end_date, frequency="M")
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assert len(d) == 11
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assert datetime.datetime(2020, 2, 29) in d
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assert datetime.datetime(2020, 8, 31) not in d
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assert datetime.datetime(2020, 10, 29) in d
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def test_quarterly(self):
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start_date = datetime.datetime(2018, 1, 1)
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end_date = datetime.datetime(2020, 12, 31)
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d = create_date_series(start_date, end_date, frequency="Q")
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assert len(d) == 12
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d = create_date_series(start_date, end_date, frequency="Q", eomonth=True)
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assert datetime.datetime(2020, 4, 30) in d
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start_date = datetime.datetime(2020, 1, 31)
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d = create_date_series(start_date, end_date, frequency="Q")
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assert len(d) == 4
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assert datetime.datetime(2020, 2, 29) not in d
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assert max(d) == datetime.datetime(2020, 10, 31)
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start_date = datetime.datetime(2020, 2, 29)
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d = create_date_series(start_date, end_date, frequency="Q")
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assert datetime.datetime(2020, 2, 29) in d
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assert datetime.datetime(2020, 8, 31) not in d
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assert datetime.datetime(2020, 11, 29) in d
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d = create_date_series(start_date, end_date, frequency="Q", eomonth=True)
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assert datetime.datetime(2020, 11, 30) in d
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class TestFincalBasic:
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def test_creation(self):
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data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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assert len(time_series) == 50
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assert isinstance(time_series.frequency, Frequency)
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assert time_series.frequency.days == 1
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ffill_data = time_series.ffill()
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assert len(ffill_data) == 50
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data = create_test_data(frequency="D", eomonth=False, n=500, gaps=0.1, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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assert len(time_series) == 450
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def test_fill(self):
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data = create_test_data(frequency="D", eomonth=False, n=500, gaps=0.1, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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ffill_data = time_series.ffill()
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assert len(ffill_data) >= 498
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ffill_data = time_series.ffill(inplace=True)
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assert ffill_data is None
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assert len(time_series) >= 498
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data = create_test_data(frequency="D", eomonth=False, n=500, gaps=0.1, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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bfill_data = time_series.bfill()
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assert len(bfill_data) >= 498
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bfill_data = time_series.bfill(inplace=True)
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assert bfill_data is None
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assert len(time_series) >= 498
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data = [("2021-01-01", 220), ("2021-01-02", 230), ("2021-03-04", 240)]
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ts = TimeSeries(data, frequency="D")
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ff = ts.ffill()
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assert ff["2021-01-03"][1] == 230
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bf = ts.bfill()
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assert bf["2021-01-03"][1] == 240
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def test_iloc_slicing(self):
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data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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assert time_series.iloc[0] is not None
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assert time_series.iloc[:3] is not None
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assert time_series.iloc[5:7] is not None
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assert isinstance(time_series.iloc[0], tuple)
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assert isinstance(time_series.iloc[10:20], list)
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assert len(time_series.iloc[10:20]) == 10
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def test_key_slicing(self):
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data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
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time_series = TimeSeries(data, frequency="D")
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available_date = time_series.iloc[5][0]
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assert time_series[available_date] is not None
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assert isinstance(time_series["dates"], Series)
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assert isinstance(time_series["values"], Series)
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assert len(time_series.dates) == 50
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assert len(time_series.values) == 50
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def test_returns_calc(self):
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data = [
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('2020-01-01', 10),
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('2020-02-01', 12),
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('2020-03-01', 14),
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('2020-04-01', 16),
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('2020-05-01', 18),
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('2020-06-01', 20),
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('2020-07-01', 22),
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('2020-08-01', 24),
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('2020-09-01', 26),
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('2020-10-01', 28),
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('2020-11-01', 30),
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('2020-12-01', 32),
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('2021-01-01', 34)
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]
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ts = TimeSeries(data, frequency='M')
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returns = ts.calculate_returns("2021-01-01", compounding=False, interval_type='years', interval_value=1)
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assert returns == 2.4
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returns = ts.calculate_returns("2020-04-01", compounding=False, interval_type='months', interval_value=3)
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assert round(returns, 4) == 0.6
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returns = ts.calculate_returns("2020-04-01", compounding=True, interval_type='months', interval_value=3)
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assert round(returns, 4) == 5.5536
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returns = ts.calculate_returns("2020-04-01", compounding=False, interval_type='days', interval_value=90)
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assert round(returns, 4) == 0.6
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returns = ts.calculate_returns("2020-04-01", compounding=True, interval_type='days', interval_value=90)
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assert round(returns, 4) == 5.727
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returns = ts.calculate_returns("2020-04-10", compounding=True, interval_type='days', interval_value=90)
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assert round(returns, 4) == 5.727
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