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6 Commits

Author SHA1 Message Date
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50c423611d added tests for returns 2022-02-24 23:24:20 +05:30
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308a4f1abb changed years to any period in return calc 2022-02-24 22:38:53 +05:30
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0fbca4ae4c modified return calculation to include motnhs and days 2022-02-24 11:28:37 +05:30
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66ccd2a3f8 added interval_to_years function 2022-02-24 11:28:16 +05:30
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d9ec9b508b added tests for str & repr 2022-02-24 10:11:58 +05:30
23882b2380 value test for ffill and bfill 2022-02-24 09:18:56 +05:30
4 changed files with 128 additions and 9 deletions

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@ -114,6 +114,18 @@ def _parse_date(date: str, date_format: str = None):
return date
def _interval_to_years(interval_type: Literal['years', 'months', 'day'], interval_value: int) -> int:
"""Converts any time period to years for use with compounding functions"""
day_conversion_factor = {
'years': 1,
'months': 12,
'days': 365
}
years = interval_value/day_conversion_factor[interval_type]
return years
class _IndexSlicer:
"""Class to create a slice using iloc in TimeSeriesCore"""

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@ -1,11 +1,17 @@
from __future__ import annotations
import datetime
from typing import List, Union
from typing import List, Literal, Union
from dateutil.relativedelta import relativedelta
from .core import AllFrequencies, TimeSeriesCore, _parse_date, _preprocess_match_options
from .core import (
AllFrequencies,
TimeSeriesCore,
_interval_to_years,
_parse_date,
_preprocess_match_options,
)
def create_date_series(
@ -120,7 +126,8 @@ class TimeSeries(TimeSeriesCore):
prior_match: str = "closest",
closest: str = "previous",
compounding: bool = True,
years: int = 1,
interval_type: Literal['years', 'months', 'days'] = 'years',
interval_value: int = 1,
date_format: str = None
) -> float:
"""Method to calculate returns for a certain time-period as on a particular date
@ -172,7 +179,7 @@ class TimeSeries(TimeSeriesCore):
raise ValueError("As on date not found")
as_on += as_on_delta
prev_date = as_on - relativedelta(years=years)
prev_date = as_on - relativedelta(**{interval_type: interval_value})
while True:
previous = self.data.get(prev_date, None)
if previous is not None:
@ -183,6 +190,7 @@ class TimeSeries(TimeSeriesCore):
returns = current / previous
if compounding:
years = _interval_to_years(interval_type, interval_value)
returns = returns ** (1 / years)
return returns - 1
@ -195,7 +203,8 @@ class TimeSeries(TimeSeriesCore):
prior_match: str = "closest",
closest: str = "previous",
compounding: bool = True,
years: int = 1,
interval_type: Literal['years', 'months', 'days'] = 'years',
interval_value: int = 1,
date_format: str = None
) -> List[tuple]:
"""Calculates the rolling return"""
@ -220,7 +229,8 @@ class TimeSeries(TimeSeriesCore):
returns = self.calculate_returns(
as_on=i,
compounding=compounding,
years=years,
interval_type=interval_type,
interval_value=interval_value,
as_on_match=as_on_match,
prior_match=prior_match,
closest=closest,

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@ -1,5 +1,6 @@
import datetime
from typing import Mapping
import random
from typing import Literal, Mapping, Sequence
from fincal.core import AllFrequencies, Frequency, Series, TimeSeriesCore
from fincal.fincal import create_date_series
@ -15,6 +16,48 @@ class TestFrequency:
assert D.freq_type == 'days'
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 TestAllFrequencies:
def test_attributes(self):
assert hasattr(AllFrequencies, 'D')
@ -53,6 +96,15 @@ class TestSeries:
class TestTimeSeriesCore:
data = [('2021-01-01', 220), ('2021-02-01', 230), ('2021-03-01', 240)]
def test_repr_str(self):
ts = TimeSeriesCore(self.data, frequency='M')
assert str(ts) in repr(ts).replace('\t', ' ')
data = create_test_data(frequency="D", eomonth=False, n=50, gaps=0, month_position="start", date_as_str=True)
ts = TimeSeriesCore(data, frequency="D")
assert '...' in str(ts)
assert '...' in repr(ts)
def test_creation(self):
ts = TimeSeriesCore(self.data, frequency='M')
assert isinstance(ts, TimeSeriesCore)

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@ -115,7 +115,7 @@ class TestDateSeries:
assert datetime.datetime(2020, 11, 30) in d
class TestFincal:
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")
@ -130,7 +130,7 @@ class TestFincal:
time_series = TimeSeries(data, frequency="D")
assert len(time_series) == 450
def test_ffill(self):
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()
@ -140,6 +140,23 @@ class TestFincal:
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")
@ -159,3 +176,31 @@ class TestFincal:
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