Series tests pass data type as string

.gitignore

@@ -2,4 +2,5 @@
 .eggs
 .env
 *egg-info
-__pycache__
+__pycache__
+.vscode

my_test.py

@@ -1,16 +1,19 @@
+import datetime
 import time
+import timeit
 
 import pandas
 
-from fincal.fincal import AllFrequencies, Frequency, TimeSeries, create_date_series
+from fincal.fincal import AllFrequencies, TimeSeries, create_date_series
 
-dfd = pandas.read_csv('test_files/nav_history_daily - Copy.csv')
+dfd = pandas.read_csv('test_files/msft.csv')
 dfm = pandas.read_csv('test_files/nav_history_monthly.csv')
 dfq = pandas.read_csv('test_files/nav_history_quarterly.csv')
 
 data_d = [(i.date, i.nav) for i in dfd.itertuples()]
 data_m = [{'date': i.date, 'value': i.nav} for i in dfm.itertuples()]
 data_q = {i.date: i.nav for i in dfq.itertuples()}
+data_q.update({'14-02-2022': 93.7})
 
 tsd = TimeSeries(data_d, frequency='D')
 tsm = TimeSeries(data_m, frequency='M', date_format='%d-%m-%Y')
@@ -18,6 +21,6 @@ tsq = TimeSeries(data_q, frequency='Q', date_format='%d-%m-%Y')
 
 start = time.time()
 # ts.calculate_rolling_returns(datetime.datetime(2015, 1, 1), datetime.datetime(2022, 2, 1), years=1)
-# fdata = tsd.ffill()
+bdata = tsq.bfill()
 # rr = tsd.calculate_rolling_returns(datetime.datetime(2022, 1, 1), datetime.datetime(2022, 2, 1), years=1)
 print(time.time() - start)

test.py

@@ -0,0 +1,35 @@
+# type: ignore
+
+import datetime
+import time
+
+import pandas as pd
+
+from fincal.fincal import TimeSeries
+
+df = pd.read_csv('test_files/nav_history_daily.csv')
+df = df.sort_values(by=['amfi_code', 'date'])  # type: ignore
+data_list = [(i.date, i.nav) for i in df[df.amfi_code == 118825].itertuples()]
+
+start = time.time()
+ts_data = TimeSeries(data_list, frequency='M')
+print(f"Instantiation took {round((time.time() - start)*1000, 2)} ms")
+# ts_data.fill_missing_days()
+start = time.time()
+# ts_data.calculate_returns(as_on=datetime.datetime(2022, 1, 4), closest='next', years=1)
+rr = ts_data.calculate_rolling_returns(datetime.datetime(2015, 1, 1),
+                                       datetime.datetime(2022, 1, 21),
+                                       frequency='M',
+                                       as_on_match='next',
+                                       prior_match='previous',
+                                       closest='previous',
+                                       years=1)
+
+# ffill_data = ts_data.bfill()
+print(f"Calculation took {round((time.time() - start)*1000, 2)} ms")
+rr.sort()
+for i in rr[:10]:
+    print(i)
+# print(ffill_data)
+# print(ts_data)
+# print(repr(ts_data))

test2.py

@@ -0,0 +1,37 @@
+# type: ignore
+
+if __name__ == "__main__":
+
+    import datetime
+    import time
+
+    import pandas as pd
+
+    from fincal.fincal import TimeSeries
+
+    df = pd.read_csv('test_files/msft.csv')
+    df = df.sort_values(by='Date')  # type: ignore
+    data_list = [(i.Date, i.Close) for i in df.itertuples()]
+
+    start = time.time()
+    ts_data = TimeSeries(data_list, frequency='D', date_format='%d-%m-%Y')
+    print(f"Instantiation took {round((time.time() - start)*1000, 2)} ms")
+    # ts_data.fill_missing_days()
+    start = time.time()
+    # ts_data.calculate_returns(as_on=datetime.datetime(2022, 1, 4), closest='next', years=1)
+    rr = ts_data.calculate_rolling_returns(datetime.datetime(1994, 1, 1),
+                                        datetime.datetime(2022, 2, 17),
+                                        frequency='D',
+                                        as_on_match='next',
+                                        prior_match='previous',
+                                        closest='previous',
+                                        years=1)
+
+    # ffill_data = ts_data.bfill()
+    print(f"Calculation took {round((time.time() - start)*1000, 2)} ms")
+    rr.sort()
+    for i in rr[:10]:
+        print(i)
+    # print(ffill_data)
+    # print(ts_data)
+    # print(repr(ts_data))

test_series.py

@@ -0,0 +1,25 @@
+import datetime
+
+from fincal.core import Series
+
+s1 = Series([2.5, 6.2, 5.6, 8.4, 7.4, 1.5, 9.6, 5])
+
+dt_lst = [
+    datetime.datetime(2020, 12, 4, 0, 0),
+    datetime.datetime(2019, 5, 16, 0, 0),
+    datetime.datetime(2019, 9, 25, 0, 0),
+    datetime.datetime(2016, 2, 18, 0, 0),
+    datetime.datetime(2017, 8, 14, 0, 0),
+    datetime.datetime(2018, 1, 4, 0, 0),
+    datetime.datetime(2017, 5, 21, 0, 0),
+    datetime.datetime(2018, 7, 17, 0, 0),
+    datetime.datetime(2016, 4, 8, 0, 0),
+    datetime.datetime(2020, 1, 7, 0, 0),
+    datetime.datetime(2016, 12, 24, 0, 0),
+    datetime.datetime(2020, 6, 19, 0, 0),
+    datetime.datetime(2016, 3, 16, 0, 0),
+    datetime.datetime(2017, 4, 25, 0, 0),
+    datetime.datetime(2016, 7, 10, 0, 0)
+]
+
+s2 = Series(dt_lst)

tests/test_core.py

@@ -40,10 +40,10 @@ class TestAllFrequencies:
 
 class TestSeries:
     def test_creation(self):
-        series = Series([1, 2, 3, 4, 5, 6, 7], data_type=int)
+        series = Series([1, 2, 3, 4, 5, 6, 7], data_type='number')
         assert series.dtype == float
         assert series[2] == 3
 
-        dates = create_date_series('2021-01-01', '2021-01-31', 'D')
-        series = Series(dates, data_type=datetime.datetime)
-        assert Series.dtype == datetime.datetime
+        dates = create_date_series('2021-01-01', '2021-01-31', frequency='D')
+        series = Series(dates, data_type='date')
+        assert series.dtype == datetime.datetime