imports relative

dios/__init__.py

 
-from dios.lib import *
-from dios.dios import *
+from .lib import *
+from .dios import *
 

dios/dios.py

-from dios.operators import OP_MAP as _OP_MAP
+from .operators import OP_MAP as _OP_MAP
 
-from dios.lib import *
-from dios.lib import _CAST_POLICIES, _itype_le, _throw_MixedItype_err_or_warn
+from .lib import *
+from .lib import _CAST_POLICIES, _itype_le, _throw_MixedItype_err_or_warn
 
 import pandas as pd
 import numpy as np
@@ -49,12 +49,12 @@ def _is_bool_series(obj):
 
 class DictOfSeries:
     """
-    DictionaryOfSeries is a collection of pd.Series's which aim to be as close as possible similar to
+    DictOfSeries is a collection of pd.Series's which aim to be as close as possible similar to
     pd.DataFrame. The advantage over pd.DataFrame is, that every `column` has its own row-index,
     unlike the former, which provide a single row-index for all columns. This solves problems with
     unaligned pd.Series.
 
-    DictionaryOfSeries:
+    DictOfSeries:
       - ``dios['a']``       indexing with single label, work on columns, return series
       - ``dios[iterable]``  indexing with list, work on columns, return dios
       - ``dios[slice]``     indexing with slice, work on (all) index'es, return dios
@@ -224,7 +224,7 @@ class DictOfSeries:
             raise KeyError(f"{key}. tuples are not allowed")
 
         elif _is_hashable(key):
-            if isinstance(value, pd.Series):
+            if isinstance(value, pd.Series) or key not in self.columns:
                 self._insert(key, value)
             else:
                 self._data.at[key][:] = value
@@ -249,27 +249,27 @@ class DictOfSeries:
 
     @property
     def loc(self):
-        from dios.locator import _LocIndexer
+        from .locator import _LocIndexer
         return _LocIndexer(self)
 
     @property
     def iloc(self):
-        from dios.locator import _iLocIndexer
+        from .locator import _iLocIndexer
         return _iLocIndexer(self)
 
     @property
     def aloc(self):
-        from dios.locator import _aLocIndexer
+        from .locator import _aLocIndexer
         return _aLocIndexer(self)
 
     @property
     def at(self):
-        from dios.locator import _AtIndexer
+        from .locator import _AtIndexer
         return _AtIndexer(self)
 
     @property
     def iat(self):
-        from dios.locator import _iAtIndexer
+        from .locator import _iAtIndexer
         return _iAtIndexer(self)
 
     @property
@@ -479,7 +479,7 @@ class DictOfSeries:
 
 def pprint_dios(dios, max_rows=10, max_cols=2, delim='  '):
     if dios.empty:
-        return f"Empty DictionaryOfSeries\n" \
+        return f"Empty DictOfSeries\n" \
                f"Columns: {dios.columns.to_list()}"
 
     sstr = []

dios/lib.py

@@ -260,7 +260,7 @@ dios_options = {
 
 
 def _throw_MixedItype_err_or_warn(itype):
-    msg = f"'{itype.repr}'. Using a non-unique Itype for a DictionaryOfSeries, is not recommend. " \
+    msg = f"'{itype.repr}'. Using a non-unique Itype for a DictOfSeries, is not recommend. " \
           f"As soon as series \nwith different index types are inserted, selecting and slicing data will " \
           f"almost always fail. You are hereby warned!"
     if dios_options[OptsFields.mixed_itype_warn_policy] in ['ignore', Opts.itype_ignore]:

dios/locator.py

-from dios.dios import (
+from .dios import (
     _is_dios_like,
     _is_bool_series,
     _is_list_like_not_nested,

profiling/__init__.py

 from .generate_testsets import *
-from profiling.performance import find_index_range, gen_random_timestamps
+from .performance import find_index_range, gen_random_timestamps
 

profiling/generate_testsets.py

@@ -3,7 +3,7 @@ import time
 import pandas as pd
 import numpy as np
 import datetime as dt
-from dios import dios
+from ..dios import DictOfSeries
 import pickle
 import os
 
@@ -12,7 +12,7 @@ var_prefix = 'var'
 
 def _gen_testset(rowsz, colsz, freq='1min', disalign=True, randstart=True):
     df = pd.DataFrame()
-    dos = dios.DictOfSeries()
+    dos = DictOfSeries()
     start = dt.datetime.strptime("2000-01-01 00:00:00", "%Y-%m-%d %H:%M:%S")
     times = pd.date_range(periods=rowsz, start=start, freq=freq)
 

profiling/memory.py

 import gc
-from profiling.generate_testsets import get_random_df_and_dios
+from .generate_testsets import get_random_df_and_dios
 
 
 def calc_mem(rows, cols, shifted=False, dtypesz=(64 / 8)):

profiling/performance.py

 import pandas as pd
 import numpy as np
 import time
-from profiling.generate_testsets import get_testset, var_prefix
+from .generate_testsets import get_testset, var_prefix
 
 profile_assignment = False
 

test/run_dios.py

 
-from dios import *
+from ..dios import *
 import numpy as np
 
 if __name__ == '__main__':

test/test__getitem__.py

-from dios import *
-from test.test_setup import *
+from ..dios import *
+from .test_setup import *
 from pandas.core.dtypes.common import is_scalar
 
 # s1 = pd.Series(range(10), index=range(10))

test/test__setitem__.py

-from dios import *
-from test.test_setup import *
+from ..dios import *
+from .test_setup import *
 import pytest
 
 s1 = pd.Series(range(10), index=range(10))

test/test_df_like.py

 #!/usr/bin/env python
 import pytest
-from dios import *
+from ..dios import *
 
 import pandas as pd
 from pandas.core.dtypes.common import is_dict_like, is_nested_list_like

test/test_dflike__setget__.py

-from dios import *
-from test.test_setup import *
+from ..dios import *
+from .test_setup import *
 import pytest
 
 

test/test_dios_old.py

-from dios import *
-from profiling import *
+from ..dios import *
+from ..profiling import *
 import pandas as pd
 import datetime as dt
 import numpy as np

test/test_magic_methods.py

-from test.test_setup import *
+from .test_setup import *
 
 
 def test__len__(datetime_series, maxlen=10):

test/test_methods.py

-from test.test_setup import *
+from .test_setup import *
 
 
 def test_copy_copy_empty(getDtDiosAligned):

test/test_ops.py

 #!/usr/bin/env python
-from test.test_setup import *
-from dios.operators import *
+from .test_setup import *
+from ..dios.operators import *
 
 
 __author__ = "Bert Palm"

test/test_setup.py

 import pytest
-from dios import *
-from dios.operators import _OP1_MAP, _OP2_DIV_MAP, _OP2_ARITH_MAP, _OP2_BOOL_MAP, _OP2_COMP_MAP
+from ..dios import *
+from ..dios.operators import _OP1_MAP, _OP2_DIV_MAP, _OP2_ARITH_MAP, _OP2_BOOL_MAP, _OP2_COMP_MAP
 import pandas as pd
 import numpy as np
 from copy import deepcopy