changed init to super().__init__

getting started with setitem and sync

fincal/core.py

@@ -237,7 +237,7 @@ class TimeSeriesCore(UserDict):
 
         data = _preprocess_timeseries(data, date_format=date_format)
 
-        self.data = dict(data)
+        super().__init__(dict(data))
         if len(self.data) != len(data):
             print("Warning: The input data contains duplicate dates which have been ignored.")
         self.frequency: Frequency = getattr(AllFrequencies, frequency)
@@ -364,6 +364,9 @@ class TimeSeriesCore(UserDict):
 
         raise TypeError(f"Invalid type {repr(type(key).__name__)} for slicing.")
 
+    # def __setitem__(self, key, value):
+    #     pass
+
     def __iter__(self):
         self.n = 0
         return self

fincal/fincal.py

@@ -319,8 +319,7 @@ class TimeSeries(TimeSeriesCore):
     def calculate_rolling_returns(
         self,
         from_date: datetime.date | str,
-        to_date: datetime.date,
-        str,
+        to_date: datetime.date | str,
         frequency: Literal["D", "W", "M", "Q", "H", "Y"] = None,
         as_on_match: str = "closest",
         prior_match: str = "closest",
@@ -607,6 +606,26 @@ class TimeSeries(TimeSeriesCore):
 
         return output_ts
 
+    def sync(self, other: TimeSeries, fill_method: Literal["ffill", "bfill"] = "ffill"):
+        """Synchronize two TimeSeries objects
+
+        This will ensure that both time series have the same frequency and same set of dates.
+        The frequency will be set to the higher of the two objects.
+        Dates will be taken from the class on which the method is called.
+        """
+
+        if not isinstance(other, TimeSeries):
+            raise TypeError("Only objects of type TimeSeries can be passed for sync")
+
+        if self.frequency.days > other.frequency.days:
+            other = other.expand(to_frequency=self.frequency.symbol, method=fill_method)
+        if self.frequency.days < other.frequency.days:
+            self = self.expand(to_frequency=other.frequency.symbol, method=fill_method)
+
+        for dt, val in self.data.items():
+            if dt not in other:
+                pass  # Need to create setitem first before implementing this
+
 
 def _preprocess_csv(file_path: str | pathlib.Path, delimiter: str = ",", encoding: str = "utf-8") -> List[list]:
     """Preprocess csv data"""

fincal/utils.py

@@ -1,6 +1,6 @@
 import datetime
 from dataclasses import dataclass
-from typing import Iterable, List, Literal, Mapping, Sequence, Tuple
+from typing import List, Literal, Mapping, Sequence, Tuple
 
 from .exceptions import DateNotFoundError, DateOutOfRangeError
 
@@ -32,7 +32,7 @@ def _parse_date(date: str, date_format: str = None):
 
 
 def _preprocess_timeseries(
-    data: Sequence[Iterable[str | datetime.datetime, float]]
+    data: Sequence[Tuple[str | datetime.datetime, float]]
     | Sequence[Mapping[str | datetime.datetime, float]]
     | Mapping[str | datetime.datetime, float],
     date_format: str,