Use lists in import_ids dataframe indexing to clean up warnings (#105)

* Added Brendan's tests - passing with warnings

* Applied Brendan's fix - fixes warnings, but breaks in default-argument case

* fix default issue + some cleanup

nfl_data_py/__init__.py

@@ -1,15 +1,15 @@
 name = 'nfl_data_py'
 
-import datetime
 import os
 import logging
-from concurrent.futures import ThreadPoolExecutor, as_completed
+import datetime
 from warnings import warn
+from typing import Iterable
+from concurrent.futures import ThreadPoolExecutor, as_completed
 
-import appdirs
 import numpy
 import pandas
-from typing import Iterable
+import appdirs
 
 # module level doc string
 __doc__ = """
@@ -735,52 +735,32 @@ def import_ids(columns=None, ids=None):
     """Import mapping table of ids for most major data providers
     
     Args:
-        columns (List[str]): list of columns to return
-        ids (List[str]): list of specific ids to return
+        columns (Iterable[str]): list of columns to return
+        ids (Iterable[str]): list of specific ids to return
         
     Returns:
         DataFrame
     """
-
-    # create list of id options
-    avail_ids = ['mfl_id', 'sportradar_id', 'fantasypros_id', 'gsis_id', 'pff_id',
-       'sleeper_id', 'nfl_id', 'espn_id', 'yahoo_id', 'fleaflicker_id',
-       'cbs_id', 'rotowire_id', 'rotoworld_id', 'ktc_id', 'pfr_id',
-       'cfbref_id', 'stats_id', 'stats_global_id', 'fantasy_data_id']
-    avail_sites = [x[:-3] for x in avail_ids]
-
-    # check variable types
-    if columns is None:
-        columns = []
-
-    if ids is None:
-        ids = []
 
-    if not isinstance(columns, list):
-        raise ValueError('columns variable must be list.')
-
-    if not isinstance(ids, list):
-        raise ValueError('ids variable must be list.')
-
-    # confirm id is in table
-    if False in [x in avail_sites for x in ids]:
-        raise ValueError('ids variable can only contain ' + ', '.join(avail_sites))
+    columns = columns or []
+    if not isinstance(columns, Iterable):
+        raise ValueError('columns argument must be a list.')
+
+    ids = ids or []
+    if not isinstance(ids, Iterable):
+        raise ValueError('ids argument must be a list.')
 
-    # import data
-    df = pandas.read_csv(r'https://raw.githubusercontent.com/dynastyprocess/data/master/files/db_playerids.csv')
+    df = pandas.read_csv("https://raw.githubusercontent.com/dynastyprocess/data/master/files/db_playerids.csv")
 
-    rem_cols = [x for x in df.columns if x not in avail_ids]
-    tgt_ids = [x + '_id' for x in ids]
-
-    # filter df to just specified columns
-    if len(columns) > 0 and len(ids) > 0:
-        df = df[set(tgt_ids + columns)]
-    elif len(columns) > 0 and len(ids) == 0:
-        df = df[set(avail_ids + columns)]
-    elif len(columns) == 0 and len(ids) > 0:
-        df = df[set(tgt_ids + rem_cols)]
+    id_cols = [c for c in df.columns if c.endswith('_id')]
+    non_id_cols = [c for c in df.columns if not c.endswith('_id')]
 
-    return df
+    # filter df to just specified ids + columns
+    ret_ids = [x + '_id' for x in ids] or id_cols
+    ret_cols = columns or non_id_cols
+    ret_columns = list(set([*ret_ids, *ret_cols]))
+
+    return df[ret_columns]
 
 
 def import_contracts():

nfl_data_py/tests/nfl_test.py

@@ -167,6 +167,29 @@ def test_is_df_with_data(self):
         s = nfl.import_ids()
         self.assertEqual(True, isinstance(s, pd.DataFrame))
         self.assertTrue(len(s) > 0)
+
+    def test_import_using_ids(self):
+        ids = ["espn", "yahoo", "gsis"]
+        s = nfl.import_ids(ids=ids)
+        self.assertTrue(all([f"{id}_id" in s.columns for id in ids]))
+
+    def test_import_using_columns(self):
+        ret_columns = ["name", "birthdate", "college"]
+        not_ret_columns = ["draft_year", "db_season", "team"]
+        s = nfl.import_ids(columns=ret_columns)
+        self.assertTrue(all([column in s.columns for column in ret_columns]))
+        self.assertTrue(all([column not in s.columns for column in not_ret_columns]))
+
+    def test_import_using_ids_and_columns(self):
+        ret_ids = ["espn", "yahoo", "gsis"]
+        ret_columns = ["name", "birthdate", "college"]
+        not_ret_ids = ["cfbref_id", "pff_id", "prf_id"]
+        not_ret_columns = ["draft_year", "db_season", "team"]
+        s = nfl.import_ids(columns=ret_columns, ids=ret_ids)
+        self.assertTrue(all([column in s.columns for column in ret_columns]))
+        self.assertTrue(all([column not in s.columns for column in not_ret_columns]))
+        self.assertTrue(all([f"{id}_id" in s.columns for id in ret_ids]))
+        self.assertTrue(all([f"{id}_id" not in s.columns for id in not_ret_ids]))
 
 class test_ngs(TestCase):
     def test_is_df_with_data(self):