added tests for str & repr
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@ -1,5 +1,6 @@
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import datetime
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from typing import Mapping
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import random
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from typing import Literal, Mapping, Sequence
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from fincal.core import AllFrequencies, Frequency, Series, TimeSeriesCore
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from fincal.fincal import create_date_series
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@ -15,6 +16,48 @@ class TestFrequency:
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assert D.freq_type == 'days'
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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 TestAllFrequencies:
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def test_attributes(self):
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assert hasattr(AllFrequencies, 'D')
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@ -53,6 +96,15 @@ class TestSeries:
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class TestTimeSeriesCore:
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data = [('2021-01-01', 220), ('2021-02-01', 230), ('2021-03-01', 240)]
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def test_repr_str(self):
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ts = TimeSeriesCore(self.data, frequency='M')
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assert str(ts) in repr(ts).replace('\t', ' ')
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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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ts = TimeSeriesCore(data, frequency="D")
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assert '...' in str(ts)
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assert '...' in repr(ts)
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def test_creation(self):
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ts = TimeSeriesCore(self.data, frequency='M')
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assert isinstance(ts, TimeSeriesCore)
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