refactoring

Author: Alexd14

nusa_alphalens/__init__.py

@@ -2,11 +2,12 @@
 from . import plotting
 from . import tears
 from . import utils
+from . import nusa
 
 from ._version import get_versions
 
 
 __version__ = get_versions()['version']
 del get_versions
 
-__all__ = ['performance', 'plotting', 'tears', 'utils']
+__all__ = ['performance', 'plotting', 'tears', 'utils', 'nusa']

nusa_alphalens/nusa.py

@@ -1,14 +1,14 @@
-import pandas as pd
+import duckdb
 import logging
 
+import pandas as pd
+
 from typing import List, Optional, Union
 
-import duckdb
 import pandas_market_calendars as mcal
 
 logging.basicConfig(format='%(message)s ::: %(asctime)s', datefmt='%I:%M:%S %p')
 
-
 #
 # Adjusting pricing data
 #
@@ -81,6 +81,7 @@ def _adjust_field(field: str, table: str) -> str:
 
     return ''
 
+
 #
 # Adjusting data for universe
 #
@@ -140,7 +141,7 @@ def add_index_info(self, index_constitutes: pd.DataFrame, start_date: Union[pd.T
 
         # will throw an error if there are duplicate self.__id_col
         _handle_duplicates(df=index_constitutes, out_type='ValueError', name='The column symbols',
-                          drop=False, subset=[self.__id_col])
+                           drop=False, subset=[self.__id_col])
 
         # seeing if we have to convert from and thru to series of timestamps
         if date_format != '':
@@ -305,6 +306,11 @@ def _check_columns(needed: List[str], df: pd.DataFrame, index_columns: bool = Tr
     return df
 
 
+#
+# utility
+#
+
+
 def _handle_duplicates(df: pd.DataFrame, out_type: str, name: str, drop: bool = False,
                        subset: List[any] = None) -> pd.DataFrame:
     """
@@ -339,10 +345,3 @@ def _handle_duplicates(df: pd.DataFrame, out_type: str, name: str, drop: bool =
 
     if drop:
         return df
-
-
-if __name__ == '__main__':
-    df = pd.read_csv(
-        '/Users/alex/Desktop/WRDS/CRSP/Annual Update/Stock : Security Files/Daily Stock File/Daily Stock File 29251231-20211231.gz',
-        nrows=1000).drop('cfacshr', axis=1)
-    print(adjust_crsp_data(df))

setup.py

@@ -34,8 +34,8 @@
 if __name__ == "__main__":
     setup(
         name='nusa_alphalens',
-        version=versioneer.get_version(),
-        cmdclass=versioneer.get_cmdclass(),
+        version='0.5.0',#versioneer.get_version(),
+        #cmdclass=versioneer.get_cmdclass(),
         description='Performance analysis of predictive (alpha) stock factors',
         author='Quantopian Inc.',
         author_email='opensource@quantopian.com',
@@ -61,4 +61,5 @@
         url='https://github.com/quantopian/alphalens',
         install_requires=install_reqs,
         extras_require=extra_reqs,
+        download_url='https://github.com/Northeastern-Systematic-Alpha/alphalens/archive/refs/tags/v0.5.0.tar.gz'
     )