Merge pull request #220 from nalepae/revert-resample

Revert "Add `parallel_apply` for `Resampler` class (#211)"

Author: nalepae

pandarallel/core.py

@@ -13,7 +13,6 @@
 from pandas.core.groupby import DataFrameGroupBy as PandaDataFrameGroupBy
 from pandas.core.window.expanding import ExpandingGroupby as PandasExpandingGroupby
 from pandas.core.window.rolling import RollingGroupby as PandasRollingGroupby
-from pandas.core.resample import Resampler as PandasResampler
 
 from .data_types import (
     DataFrame,
@@ -23,7 +22,6 @@
     RollingGroupBy,
     Series,
     SeriesRolling,
-    Resampler
 )
 from .progress_bars import ProgressBarsType, get_progress_bars, progress_wrapper
 from .utils import WorkerStatus
@@ -556,8 +554,3 @@ def initialize(
         pd.core.window.Rolling.parallel_apply = parallelize(
             nb_workers, SeriesRolling.Apply, progress_bars_in_user_defined_function
         )
-
-        # Resampler
-        PandasResampler.parallel_apply = parallelize(
-            nb_workers, Resampler.Apply, progress_bars_in_user_defined_function
-        )

pandarallel/data_types/__init__.py

@@ -5,4 +5,3 @@
 from .generic import DataType
 from .series import Series
 from .series_rolling import SeriesRolling
-from .resampler import Resampler

pandarallel/data_types/resampler.py

@@ -93,7 +93,6 @@ def func(x):
 @pytest.fixture()
 def func_dataframe_groupby_apply():
     def func(df):
-        import math
         dum = 0
         for item in df.b:
             dum += math.log10(math.sqrt(math.exp(item**2)))
@@ -157,46 +156,6 @@ def func(x):
     return dict(named=func, anonymous=lambda x: x**2)[request.param]
 
 
-@pytest.fixture()
-def func_dataframe_resampler_apply():
-    def func(df):
-        import math
-        dum = 0
-        for item in df.b:
-            dum += math.log10(math.sqrt(math.exp(item**2)))
-
-        return dum / len(df.b)
-
-    return func
-
-
-@pytest.fixture()
-def func_dataframe_resampler_apply_complex():
-    def func(df):
-        return pd.DataFrame(
-            [[df.b.mean(), df.b.min(), df.b.max()]],
-            columns=["b_mean", "b_min", "b_max"],
-        )
-
-    return func
-
-
-@pytest.fixture()
-def func_dataframe_resampler_apply_series():
-    def func(df):
-        return df.iloc[0]
-
-    return func
-
-
-@pytest.fixture()
-def func_series_resampler_apply():
-    def func(x):
-        return x.sum()
-
-    return func
-
-
 @pytest.fixture
 def pandarallel_init(progress_bar, use_memory_fs):
     pandarallel.initialize(
@@ -397,69 +356,3 @@ def test_dataframe_axis_1_no_reduction(
     res_parallel = df.parallel_apply(func_dataframe_apply_axis_1_no_reduce, axis=1)
 
     assert res.equals(res_parallel)
-
-    
-def test_dataframe_resampler_apply(
-    pandarallel_init, func_dataframe_resampler_apply, df_size
-):
-    df = pd.DataFrame(
-        dict(
-            b=np.random.rand(df_size),
-            c=np.random.rand(df_size),
-        ),
-        index=pd.to_datetime(np.arange(df_size), unit="m")
-    )
-
-    if pd.__version__ != "1.0.5":
-        res = df.resample("h").apply(func_dataframe_resampler_apply)
-        res_parallel = df.resample("h").parallel_apply(func_dataframe_resampler_apply)
-        assert res.equals(res_parallel)
-    else:
-        with pytest.raises(AttributeError):
-            res = df.resample("h").apply(func_dataframe_resampler_apply)
-
-    
-def test_dataframe_resampler_apply_complex(
-    pandarallel_init, func_dataframe_resampler_apply_complex, df_size
-):
-    df = pd.DataFrame(
-        dict(b=np.random.rand(df_size)),
-        index=pd.to_datetime(np.arange(df_size), unit="m")
-    )
-
-    if pd.__version__ != "1.0.5":
-        res = df.resample("h").apply(func_dataframe_resampler_apply_complex)
-        res_parallel = df.resample("h").parallel_apply(func_dataframe_resampler_apply_complex)
-        assert res.equals(res_parallel)
-    else:
-        with pytest.raises(AttributeError):
-            res = df.resample("h").apply(func_dataframe_resampler_apply_complex)
-
-
-def test_dataframe_resampler_apply_series(
-    pandarallel_init, func_dataframe_resampler_apply_series, df_size
-):
-    df = pd.DataFrame(
-        dict(
-            b=np.random.rand(df_size),
-            c=np.random.rand(df_size),
-        ),
-        index=pd.to_datetime(np.arange(df_size), unit="m")
-    )
-
-
-    res = df.resample("h").apply(func_dataframe_resampler_apply_series)
-    res_parallel = df.resample("h").parallel_apply(func_dataframe_resampler_apply_series)
-    assert res.equals(res_parallel)
-
-def test_series_resampler_apply(
-    pandarallel_init, func_series_resampler_apply, df_size
-):
-    df = pd.Series(
-        np.random.rand(df_size),
-        index=pd.to_datetime(np.arange(df_size), unit="m")
-    )
-
-    res = df.resample("h").apply(func_series_resampler_apply)
-    res_parallel = df.resample("h").parallel_apply(func_series_resampler_apply)
-    assert res.equals(res_parallel)