implemented sync method

README.md

@@ -26,7 +26,7 @@ Fincal aims to simplify things by allowing you to:
 - [ ] Convert to dict
 - [ ] Convert to list of dicts
 ### Fincal features
-- [ ] Sync two TimeSeries
+- [x] Sync two TimeSeries
 - [x] Average rolling return
 - [ ] Sharpe ratio
 - [ ] Jensen's Alpha
@@ -35,4 +35,5 @@ Fincal aims to simplify things by allowing you to:
 
 ### Pending implementation
 - [ ] Use limit parameter in ffill and bfill
-- [ ] Implementation of ffill and bfill may be incorrect inside expand, check and correct
+- [x] Implementation of ffill and bfill may be incorrect inside expand, check and correct
+- [ ] Implement interpolation in expand

fincal/core.py

@@ -213,7 +213,7 @@ class TimeSeriesCore(UserDict):
 
     def __init__(
         self,
-        data: List[Iterable] | Mapping,
+        ts_data: List[Iterable] | Mapping,
         frequency: Literal["D", "W", "M", "Q", "H", "Y"],
         date_format: str = "%Y-%m-%d",
     ):
@@ -221,7 +221,7 @@ class TimeSeriesCore(UserDict):
 
         Parameters
         ----------
-        data : List[Iterable] | Mapping
+        ts_data : List[Iterable] | Mapping
             Time Series data in the form of list of tuples or dictionary.
             The first element of each tuple should be a date and second element should be a value.
             In case of dictionary, the key should be the date.
@@ -235,10 +235,10 @@ class TimeSeriesCore(UserDict):
             Required only if the first argument of tuples is a string. Otherwise ignored.
         """
 
-        data = _preprocess_timeseries(data, date_format=date_format)
+        ts_data = _preprocess_timeseries(ts_data, date_format=date_format)
 
-        super().__init__(dict(data))
+        super().__init__(dict(ts_data))
-        if len(self.data) != len(data):
+        if len(self.data) != len(ts_data):
             print("Warning: The input data contains duplicate dates which have been ignored.")
         self.frequency: Frequency = getattr(AllFrequencies, frequency)
         self.iter_num: int = -1
@@ -364,9 +364,6 @@ 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

@@ -617,14 +617,20 @@ class TimeSeries(TimeSeriesCore):
         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:
+            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():
+        new_other = {}
-            if dt not in other:
+        for dt in self.dates:
-                pass  # Need to create setitem first before implementing this
+            closest = "previous" if fill_method == "ffill" else "next"
+            if dt in other:
+                new_other[dt] = other[dt][1]
+            else:
+                new_other[dt] = other.get(dt, closest=closest)[1]
+
+        return self.__class__(new_other, frequency=other.frequency.symbol)
 
 
 def _preprocess_csv(file_path: str | pathlib.Path, delimiter: str = ",", encoding: str = "utf-8") -> List[list]: