Added tests for DateNotFoundError

Using find_closest_date function

fincal/core.py

@@ -29,6 +29,32 @@ class AllFrequencies:
     Y = Frequency("annual", "years", 1, 365, "Y")
 
 
+class DateNotFoundError(Exception):
+    """Exception to be raised when date is not found"""
+
+    def __init__(self, message, date):
+        message = f"{message}: {date}"
+        super().__init__(message)
+
+
+def _parse_date(date: str, date_format: str = None):
+    """Parses date and handles errors"""
+
+    if isinstance(date, (datetime.datetime, datetime.date)):
+        return datetime.datetime.fromordinal(date.toordinal())
+
+    if date_format is None:
+        date_format = FincalOptions.date_format
+
+    try:
+        date = datetime.datetime.strptime(date, date_format)
+    except TypeError:
+        raise ValueError("Date does not seem to be valid date-like string")
+    except ValueError:
+        raise ValueError("Date could not be parsed. Have you set the correct date format in FincalOptions.date_format?")
+    return date
+
+
 def _preprocess_timeseries(
     data: Union[
         Sequence[Iterable[Union[str, datetime.datetime, float]]],
@@ -40,37 +66,26 @@ def _preprocess_timeseries(
 ) -> List[Tuple[datetime.datetime, float]]:
     """Converts any type of list to the correct type"""
 
-    if isinstance(data, Sequence):
-        if isinstance(data[0], Mapping):
-            if len(data[0].keys()) == 2:
-                current_data = [tuple(i.values()) for i in data]
-            elif len(data[0].keys()) == 1:
-                current_data = [tuple(*i.items()) for i in data]
-            else:
-                raise TypeError("Could not parse the data")
-            current_data = _preprocess_timeseries(current_data, date_format)
-
-        elif isinstance(data[0], Sequence):
-            if isinstance(data[0][0], str):
-                current_data = []
-                for i in data:
-                    row = datetime.datetime.strptime(i[0], date_format), i[1]
-                    current_data.append(row)
-            elif isinstance(data[0][0], datetime.datetime):
-                current_data = [(i, j) for i, j in data]
-            else:
-                raise TypeError("Could not parse the data")
-        else:
-            raise TypeError("Could not parse the data")
-
-    elif isinstance(data, Mapping):
+    if isinstance(data, Mapping):
         current_data = [(k, v) for k, v in data.items()]
-        current_data = _preprocess_timeseries(current_data, date_format)
+        return _preprocess_timeseries(current_data, date_format)
+
+    if not isinstance(data, Sequence):
+        raise TypeError("Could not parse the data")
+
+    if isinstance(data[0], Sequence):
+        return sorted([(_parse_date(i, date_format), j) for i, j in data])
 
+    if not isinstance(data[0], Mapping):
+        raise TypeError("Could not parse the data")
+
+    if len(data[0]) == 1:
+        current_data = [tuple(*i.items()) for i in data]
+    elif len(data[0]) == 2:
+        current_data = [tuple(i.values()) for i in data]
     else:
         raise TypeError("Could not parse the data")
-    current_data.sort()
-    return current_data
+    return _preprocess_timeseries(current_data, date_format)
 
 
 def _preprocess_match_options(as_on_match: str, prior_match: str, closest: str) -> datetime.timedelta:
@@ -78,7 +93,7 @@ def _preprocess_match_options(as_on_match: str, prior_match: str, closest: str)
 
     deltas = {"exact": 0, "previous": -1, "next": 1}
     if closest not in deltas.keys():
-        raise ValueError(f"Invalid closest argument: {closest}")
+        raise ValueError(f"Invalid argument for closest: {closest}")
 
     as_on_match = closest if as_on_match == "closest" else as_on_match
     prior_match = closest if prior_match == "closest" else prior_match
@@ -96,33 +111,29 @@ def _preprocess_match_options(as_on_match: str, prior_match: str, closest: str)
     return as_on_delta, prior_delta
 
 
-def _parse_date(date: str, date_format: str = None):
-    """Parses date and handles errors"""
+def _find_closest_date(data, date, delta, if_not_found):
+    """Helper function to find data for the closest available date"""
 
-    if isinstance(date, (datetime.datetime, datetime.date)):
-        return datetime.datetime.fromordinal(date.toordinal())
+    row = data.get(date, None)
+    if row is not None:
+        return date, row
 
-    if date_format is None:
-        date_format = FincalOptions.date_format
+    if delta:
+        return _find_closest_date(data, date + delta, delta, if_not_found)
 
-    try:
-        date = datetime.datetime.strptime(date, date_format)
-    except TypeError:
-        raise ValueError("Date does not seem to be valid date-like string")
-    except ValueError:
-        raise ValueError("Date could not be parsed. Have you set the correct date format in FincalOptions.date_format?")
-    return date
+    if if_not_found == "fail":
+        raise DateNotFoundError("Data not found for date", date)
+    if if_not_found == "nan":
+        return date, float("NaN")
+
+    raise ValueError(f"Invalid argument for if_not_found: {if_not_found}")
 
 
-def _interval_to_years(interval_type: Literal['years', 'months', 'day'], interval_value: int) -> int:
+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]
+    year_conversion_factor = {"years": 1, "months": 12, "days": 365}
+    years = interval_value / year_conversion_factor[interval_type]
     return years
 
 

fincal/fincal.py

@@ -8,6 +8,7 @@ from dateutil.relativedelta import relativedelta
 from .core import (
     AllFrequencies,
     TimeSeriesCore,
+    _find_closest_date,
     _interval_to_years,
     _parse_date,
     _preprocess_match_options,
@@ -189,40 +190,19 @@ class TimeSeries(TimeSeriesCore):
 
         as_on = _parse_date(as_on, date_format)
         as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest)
-        original_as_on = as_on
-
-        while True:
-            current = self.data.get(as_on, None)
-            if current is not None:
-                break
-            elif not as_on_delta:
-                if if_not_found == 'fail':
-                    raise ValueError(f"As on date {original_as_on} not found")
-                elif if_not_found == 'nan':
-                    return as_on, float("NaN")
-                else:
-                    raise ValueError(f"Invalid argument for if_not_found: {if_not_found}")
-            as_on += as_on_delta
 
         prev_date = as_on - relativedelta(**{interval_type: interval_value})
-        while True:
-            previous = self.data.get(prev_date, None)
-            if previous is not None:
-                break
-            elif not prior_delta:
-                if if_not_found == 'fail':
-                    raise ValueError(f"Previous date {previous} not found")
-                elif if_not_found == 'nan':
-                    return (as_on if return_actual_date else original_as_on), float("NaN")
-                else:
-                    raise ValueError(f"Invalid argument for if_not_found: {if_not_found}")
-            prev_date += prior_delta
-
-        returns = current / previous
+        current = _find_closest_date(self.data, as_on, as_on_delta, if_not_found)
+        previous = _find_closest_date(self.data, prev_date, prior_delta, if_not_found)
+
+        if current[1] == str('nan') or previous[1] == str('nan'):
+            return as_on, float('NaN')
+
+        returns = current[1] / previous[1]
         if compounding:
             years = _interval_to_years(interval_type, interval_value)
             returns = returns ** (1 / years)
-        return (as_on if return_actual_date else original_as_on), returns - 1
+        return (current[0] if return_actual_date else as_on), returns - 1
 
     def calculate_rolling_returns(
         self,
@@ -274,13 +254,13 @@ class TimeSeries(TimeSeriesCore):
 
 if __name__ == "__main__":
     date_series = [
-        datetime.datetime(2020, 1, 1),
-        datetime.datetime(2020, 1, 2),
-        datetime.datetime(2020, 1, 3),
-        datetime.datetime(2020, 1, 4),
-        datetime.datetime(2020, 1, 7),
-        datetime.datetime(2020, 1, 8),
-        datetime.datetime(2020, 1, 9),
-        datetime.datetime(2020, 1, 10),
+        datetime.datetime(2020, 1, 11),
         datetime.datetime(2020, 1, 12),
+        datetime.datetime(2020, 1, 13),
+        datetime.datetime(2020, 1, 14),
+        datetime.datetime(2020, 1, 17),
+        datetime.datetime(2020, 1, 18),
+        datetime.datetime(2020, 1, 19),
+        datetime.datetime(2020, 1, 20),
+        datetime.datetime(2020, 1, 22),
     ]

tests/test_fincal.py

@@ -4,7 +4,7 @@ import random
 from typing import Literal, Sequence
 
 import pytest
-from fincal.core import FincalOptions, Frequency, Series
+from fincal.core import DateNotFoundError, FincalOptions, Frequency, Series
 from fincal.fincal import TimeSeries, create_date_series
 
 THIS_DIR = os.path.dirname(os.path.abspath(__file__))
@@ -209,8 +209,10 @@ class TestReturns:
         assert round(returns[1], 4) == 5.727
         returns = ts.calculate_returns("2020-04-10", compounding=True, interval_type='days', interval_value=90)
         assert round(returns[1], 4) == 5.727
-        with pytest.raises(ValueError):
+        with pytest.raises(DateNotFoundError):
             ts.calculate_returns("2020-04-10", interval_type='days', interval_value=90, as_on_match='exact')
+        with pytest.raises(DateNotFoundError):
+            ts.calculate_returns("2020-04-10", interval_type='days', interval_value=90, prior_match='exact')
 
     def test_date_formats(self):
         ts = TimeSeries(self.data, frequency='M')