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CLN: numba.prange usage #38661

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Merged
merged 1 commit into from
Dec 23, 2020
Merged

CLN: numba.prange usage #38661

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16 changes: 4 additions & 12 deletions pandas/core/groupby/numba_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,10 +89,6 @@ def generate_numba_agg_func(

numba_func = jit_user_function(func, nopython, nogil, parallel)
numba = import_optional_dependency("numba")
if parallel:
loop_range = numba.prange
else:
loop_range = range

@numba.jit(nopython=nopython, nogil=nogil, parallel=parallel)
def group_agg(
Expand All @@ -104,9 +100,9 @@ def group_agg(
num_columns: int,
) -> np.ndarray:
result = np.empty((num_groups, num_columns))
for i in loop_range(num_groups):
for i in numba.prange(num_groups):
group_index = index[begin[i] : end[i]]
for j in loop_range(num_columns):
for j in numba.prange(num_columns):
group = values[begin[i] : end[i], j]
result[i, j] = numba_func(group, group_index, *args)
return result
Expand Down Expand Up @@ -153,10 +149,6 @@ def generate_numba_transform_func(

numba_func = jit_user_function(func, nopython, nogil, parallel)
numba = import_optional_dependency("numba")
if parallel:
loop_range = numba.prange
else:
loop_range = range

@numba.jit(nopython=nopython, nogil=nogil, parallel=parallel)
def group_transform(
Expand All @@ -168,9 +160,9 @@ def group_transform(
num_columns: int,
) -> np.ndarray:
result = np.empty((len(values), num_columns))
for i in loop_range(num_groups):
for i in numba.prange(num_groups):
group_index = index[begin[i] : end[i]]
for j in loop_range(num_columns):
for j in numba.prange(num_columns):
group = values[begin[i] : end[i], j]
result[begin[i] : end[i], j] = numba_func(group, group_index, *args)
return result
Expand Down
12 changes: 2 additions & 10 deletions pandas/core/window/numba_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,17 +50,13 @@ def generate_numba_apply_func(

numba_func = jit_user_function(func, nopython, nogil, parallel)
numba = import_optional_dependency("numba")
if parallel:
loop_range = numba.prange
else:
loop_range = range

@numba.jit(nopython=nopython, nogil=nogil, parallel=parallel)
def roll_apply(
values: np.ndarray, begin: np.ndarray, end: np.ndarray, minimum_periods: int
) -> np.ndarray:
result = np.empty(len(begin))
for i in loop_range(len(result)):
for i in numba.prange(len(result)):
start = begin[i]
stop = end[i]
window = values[start:stop]
Expand Down Expand Up @@ -103,10 +99,6 @@ def generate_numba_groupby_ewma_func(
return NUMBA_FUNC_CACHE[cache_key]

numba = import_optional_dependency("numba")
if parallel:
loop_range = numba.prange
else:
loop_range = range

@numba.jit(nopython=nopython, nogil=nogil, parallel=parallel)
def groupby_ewma(
Expand All @@ -117,7 +109,7 @@ def groupby_ewma(
) -> np.ndarray:
result = np.empty(len(values))
alpha = 1.0 / (1.0 + com)
for i in loop_range(len(begin)):
for i in numba.prange(len(begin)):
start = begin[i]
stop = end[i]
window = values[start:stop]
Expand Down