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