BENCH: skip slowest tzlocal asvs (#39995)

Author: jbrockmendel

asv_bench/benchmarks/timeseries.py

@@ -97,7 +97,7 @@ def setup(self, tz):
         idx = date_range(start="1/1/2000", periods=1000, freq="H", tz=tz)
         self.df = DataFrame(np.random.randn(1000, 2), index=idx)
 
-    def time_reest_datetimeindex(self, tz):
+    def time_reset_datetimeindex(self, tz):
         self.df.reset_index()
 
 

asv_bench/benchmarks/tslibs/normalize.py

@@ -14,6 +14,7 @@
 from .tslib import (
     _sizes,
     _tzs,
+    tzlocal_obj,
 )
 
 
@@ -30,6 +31,10 @@ def setup(self, size, tz):
         dti = pd.date_range("2016-01-01", periods=10, tz=tz).repeat(size // 10)
         self.i8data = dti.asi8
 
+        if size == 10 ** 6 and tz is tzlocal_obj:
+            # tzlocal is cumbersomely slow, so skip to keep runtime in check
+            raise NotImplementedError
+
     def time_normalize_i8_timestamps(self, size, tz):
         normalize_i8_timestamps(self.i8data, tz)
 

asv_bench/benchmarks/tslibs/period.py

@@ -15,6 +15,7 @@
 from .tslib import (
     _sizes,
     _tzs,
+    tzlocal_obj,
 )
 
 try:
@@ -129,6 +130,10 @@ class TimeDT64ArrToPeriodArr:
     param_names = ["size", "freq", "tz"]
 
     def setup(self, size, freq, tz):
+        if size == 10 ** 6 and tz is tzlocal_obj:
+            # tzlocal is cumbersomely slow, so skip to keep runtime in check
+            raise NotImplementedError
+
         arr = np.arange(10, dtype="i8").repeat(size // 10)
         self.i8values = arr
 

asv_bench/benchmarks/tslibs/resolution.py

@@ -17,40 +17,33 @@
             df.loc[key] = (val.average, val.stdev)
 
 """
-from datetime import (
-    timedelta,
-    timezone,
-)
-
-from dateutil.tz import (
-    gettz,
-    tzlocal,
-)
 import numpy as np
-import pytz
 
 try:
     from pandas._libs.tslibs import get_resolution
 except ImportError:
     from pandas._libs.tslibs.resolution import get_resolution
 
+from .tslib import (
+    _sizes,
+    _tzs,
+    tzlocal_obj,
+)
+
 
 class TimeResolution:
     params = (
         ["D", "h", "m", "s", "us", "ns"],
-        [1, 100, 10 ** 4, 10 ** 6],
-        [
-            None,
-            timezone.utc,
-            timezone(timedelta(minutes=60)),
-            pytz.timezone("US/Pacific"),
-            gettz("Asia/Tokyo"),
-            tzlocal(),
-        ],
+        _sizes,
+        _tzs,
     )
     param_names = ["unit", "size", "tz"]
 
     def setup(self, unit, size, tz):
+        if size == 10 ** 6 and tz is tzlocal_obj:
+            # tzlocal is cumbersomely slow, so skip to keep runtime in check
+            raise NotImplementedError
+
         arr = np.random.randint(0, 10, size=size, dtype="i8")
         arr = arr.view(f"M8[{unit}]").astype("M8[ns]").view("i8")
         self.i8data = arr

asv_bench/benchmarks/tslibs/timestamp.py

@@ -1,30 +1,11 @@
-from datetime import (
-    datetime,
-    timedelta,
-    timezone,
-)
-
-from dateutil.tz import (
-    gettz,
-    tzlocal,
-    tzutc,
-)
+from datetime import datetime
+
 import numpy as np
 import pytz
 
 from pandas import Timestamp
 
-# One case for each type of tzinfo object that has its own code path
-#  in tzconversion code.
-_tzs = [
-    None,
-    pytz.timezone("Europe/Amsterdam"),
-    gettz("US/Central"),
-    pytz.UTC,
-    tzutc(),
-    timezone(timedelta(minutes=60)),
-    tzlocal(),
-]
+from .tslib import _tzs
 
 
 class TimestampConstruction:

asv_bench/benchmarks/tslibs/tslib.py

@@ -32,13 +32,14 @@
 except ImportError:
     from pandas._libs.tslib import ints_to_pydatetime
 
+tzlocal_obj = tzlocal()
 _tzs = [
     None,
     timezone.utc,
     timezone(timedelta(minutes=60)),
     pytz.timezone("US/Pacific"),
     gettz("Asia/Tokyo"),
-    tzlocal(),
+    tzlocal_obj,
 ]
 _sizes = [0, 1, 100, 10 ** 4, 10 ** 6]
 
@@ -53,12 +54,15 @@ class TimeIntsToPydatetime:
     # TODO: fold? freq?
 
     def setup(self, box, size, tz):
+        if box == "date" and tz is not None:
+            # tz is ignored, so avoid running redundant benchmarks
+            raise NotImplementedError  # skip benchmark
+        if size == 10 ** 6 and tz is _tzs[-1]:
+            # This is cumbersomely-slow, so skip to trim runtime
+            raise NotImplementedError  # skip benchmark
+
         arr = np.random.randint(0, 10, size=size, dtype="i8")
         self.i8data = arr
 
     def time_ints_to_pydatetime(self, box, size, tz):
-        if box == "date":
-            # ints_to_pydatetime does not allow non-None tz with date;
-            #  this will mean doing some duplicate benchmarks
-            tz = None
         ints_to_pydatetime(self.i8data, tz, box=box)

asv_bench/benchmarks/tslibs/tz_convert.py

@@ -6,6 +6,7 @@
 from .tslib import (
     _sizes,
     _tzs,
+    tzlocal_obj,
 )
 
 try:
@@ -24,16 +25,17 @@ class TimeTZConvert:
     param_names = ["size", "tz"]
 
     def setup(self, size, tz):
+        if size == 10 ** 6 and tz is tzlocal_obj:
+            # tzlocal is cumbersomely slow, so skip to keep runtime in check
+            raise NotImplementedError
+
         arr = np.random.randint(0, 10, size=size, dtype="i8")
         self.i8data = arr
 
     def time_tz_convert_from_utc(self, size, tz):
         # effectively:
         #  dti = DatetimeIndex(self.i8data, tz=tz)
         #  dti.tz_localize(None)
-        if size >= 10 ** 6 and str(tz) == "tzlocal()":
-            # asv fill will because each call takes 8+seconds
-            return
         if old_sig:
             tz_convert_from_utc(self.i8data, UTC, tz)
         else: