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import gc
import numpy as np
from pandas import (
DatetimeIndex,
Index,
IntervalIndex,
MultiIndex,
RangeIndex,
Series,
date_range,
)
class SetOperations:
params = (
["monotonic", "non_monotonic"],
["datetime", "date_string", "int", "strings", "ea_int"],
["intersection", "union", "symmetric_difference"],
)
param_names = ["index_structure", "dtype", "method"]
def setup(self, index_structure, dtype, method):
N = 10**5
dates_left = date_range("1/1/2000", periods=N, freq="min")
fmt = "%Y-%m-%d %H:%M:%S"
date_str_left = Index(dates_left.strftime(fmt))
int_left = Index(np.arange(N))
ea_int_left = Index(np.arange(N), dtype="Int64")
str_left = Index([f"i-{i}" for i in range(N)], dtype=object)
data = {
"datetime": dates_left,
"date_string": date_str_left,
"int": int_left,
"strings": str_left,
"ea_int": ea_int_left,
}
if index_structure == "non_monotonic":
data = {k: mi[::-1] for k, mi in data.items()}
data = {k: {"left": idx, "right": idx[:-1]} for k, idx in data.items()}
self.left = data[dtype]["left"]
self.right = data[dtype]["right"]
def time_operation(self, index_structure, dtype, method):
getattr(self.left, method)(self.right)
class SetDisjoint:
def setup(self):
N = 10**5
B = N + 20000
self.datetime_left = DatetimeIndex(range(N))
self.datetime_right = DatetimeIndex(range(N, B))
def time_datetime_difference_disjoint(self):
self.datetime_left.difference(self.datetime_right)
class UnionWithDuplicates:
def setup(self):
self.left = Index(np.repeat(np.arange(1000), 100))
self.right = Index(np.tile(np.arange(500, 1500), 50))
def time_union_with_duplicates(self):
self.left.union(self.right)
class Range:
def setup(self):
self.idx_inc = RangeIndex(start=0, stop=10**6, step=3)
self.idx_dec = RangeIndex(start=10**6, stop=-1, step=-3)
def time_max(self):
self.idx_inc.max()
def time_max_trivial(self):
self.idx_dec.max()
def time_min(self):
self.idx_dec.min()
def time_min_trivial(self):
self.idx_inc.min()
def time_get_loc_inc(self):
self.idx_inc.get_loc(900_000)
def time_get_loc_dec(self):
self.idx_dec.get_loc(100_000)
def time_iter_inc(self):
for _ in self.idx_inc:
pass
def time_iter_dec(self):
for _ in self.idx_dec:
pass
def time_sort_values_asc(self):
self.idx_inc.sort_values()
def time_sort_values_des(self):
self.idx_inc.sort_values(ascending=False)
class IndexEquals:
def setup(self):
idx_large_fast = RangeIndex(100_000)
idx_small_slow = date_range(start="1/1/2012", periods=1)
self.mi_large_slow = MultiIndex.from_product([idx_large_fast, idx_small_slow])
self.idx_non_object = RangeIndex(1)
def time_non_object_equals_multiindex(self):
self.idx_non_object.equals(self.mi_large_slow)
class IndexAppend:
def setup(self):
N = 10_000
self.range_idx = RangeIndex(0, 100)
self.int_idx = self.range_idx.astype(int)
self.obj_idx = self.int_idx.astype(str)
self.range_idxs = []
self.int_idxs = []
self.object_idxs = []
for i in range(1, N):
r_idx = RangeIndex(i * 100, (i + 1) * 100)
self.range_idxs.append(r_idx)
i_idx = r_idx.astype(int)
self.int_idxs.append(i_idx)
o_idx = i_idx.astype(str)
self.object_idxs.append(o_idx)
def time_append_range_list(self):
self.range_idx.append(self.range_idxs)
def time_append_int_list(self):
self.int_idx.append(self.int_idxs)
def time_append_obj_list(self):
self.obj_idx.append(self.object_idxs)
class Indexing:
params = ["String", "Float", "Int"]
param_names = ["dtype"]
def setup(self, dtype):
N = 10**6
if dtype == "String":
self.idx = Index([f"i-{i}" for i in range(N)], dtype=object)
elif dtype == "Float":
self.idx = Index(np.arange(N), dtype=np.float64)
elif dtype == "Int":
self.idx = Index(np.arange(N), dtype=np.int64)
self.array_mask = (np.arange(N) % 3) == 0
self.series_mask = Series(self.array_mask)
self.sorted = self.idx.sort_values()
half = N // 2
self.non_unique = self.idx[:half].append(self.idx[:half])
self.non_unique_sorted = self.sorted[:half].repeat(2)
self.key = self.sorted[N // 4]
def time_boolean_array(self, dtype):
self.idx[self.array_mask]
def time_boolean_series(self, dtype):
self.idx[self.series_mask]
def time_get(self, dtype):
self.idx[1]
def time_slice(self, dtype):
self.idx[:-1]
def time_slice_step(self, dtype):
self.idx[::2]
def time_get_loc(self, dtype):
self.idx.get_loc(self.key)
def time_get_loc_sorted(self, dtype):
self.sorted.get_loc(self.key)
def time_get_loc_non_unique(self, dtype):
self.non_unique.get_loc(self.key)
def time_get_loc_non_unique_sorted(self, dtype):
self.non_unique_sorted.get_loc(self.key)
class Float64IndexMethod:
# GH 13166
def setup(self):
N = 100_000
a = np.arange(N, dtype=np.float64)
self.ind = Index(a * 4.8000000418824129e-08)
def time_get_loc(self):
self.ind.get_loc(0)
class IntervalIndexMethod:
# GH 24813
params = [10**3, 10**5]
def setup(self, N):
left = np.append(np.arange(N), np.array(0))
right = np.append(np.arange(1, N + 1), np.array(1))
self.intv = IntervalIndex.from_arrays(left, right)
self.intv._engine
self.intv2 = IntervalIndex.from_arrays(left + 1, right + 1)
self.intv2._engine
self.left = IntervalIndex.from_breaks(np.arange(N))
self.right = IntervalIndex.from_breaks(np.arange(N - 3, 2 * N - 3))
def time_monotonic_inc(self, N):
self.intv.is_monotonic_increasing
def time_is_unique(self, N):
self.intv.is_unique
def time_intersection(self, N):
self.left.intersection(self.right)
def time_intersection_one_duplicate(self, N):
self.intv.intersection(self.right)
def time_intersection_both_duplicate(self, N):
self.intv.intersection(self.intv2)
class GC:
params = [1, 2, 5]
def create_use_drop(self):
idx = Index(list(range(1_000_000)))
idx._engine
def peakmem_gc_instances(self, N):
try:
gc.disable()
for _ in range(N):
self.create_use_drop()
finally:
gc.enable()
from .pandas_vb_common import setup # noqa: F401 isort:skip
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