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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2021/04/15 16:16:55 UTC
[GitHub] [spark] xinrong-databricks commented on a change in pull request #32139: [SPARK-35032][PYTHON] Port Koalas Index unit tests into PySpark
xinrong-databricks commented on a change in pull request #32139:
URL: https://github.com/apache/spark/pull/32139#discussion_r614209712
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File path: python/pyspark/pandas/tests/indexes/test_datetime.py
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@@ -0,0 +1,232 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements. See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You under the Apache License, Version 2.0
+# (the "License"); you may not use this file except in compliance with
+# the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+import datetime
+
+from distutils.version import LooseVersion
+
+import pandas as pd
+
+import pyspark.pandas as ps
+from pyspark.pandas.testing.utils import ReusedSQLTestCase, TestUtils
+
+
+class DatetimeIndexTest(ReusedSQLTestCase, TestUtils):
+ @property
+ def fixed_freqs(self):
+ return [
+ "D",
+ "H",
+ "T", # min
+ "S",
+ "L", # ms
+ "U", # us
+ # 'N' not supported
+ ]
+
+ @property
+ def non_fixed_freqs(self):
+ return ["W", "Q"]
+
+ @property
+ def pidxs(self):
+ return [
+ pd.DatetimeIndex([0]),
+ pd.DatetimeIndex(["2004-01-01", "2002-12-31", "2000-04-01"]),
+ ] + [
+ pd.date_range("2000-01-01", periods=3, freq=freq)
+ for freq in (self.fixed_freqs + self.non_fixed_freqs)
+ ]
+
+ @property
+ def kidxs(self):
+ return [ps.from_pandas(pidx) for pidx in self.pidxs]
+
+ @property
+ def idx_pairs(self):
+ return list(zip(self.kidxs, self.pidxs))
+
+ def _disallow_nanoseconds(self, f):
+ self.assertRaises(ValueError, lambda: f(freq="ns"))
+ self.assertRaises(ValueError, lambda: f(freq="N"))
+
+ def test_properties(self):
+ for kidx, pidx in self.idx_pairs:
+ self.assert_eq(kidx.year, pidx.year)
+ self.assert_eq(kidx.month, pidx.month)
+ self.assert_eq(kidx.day, pidx.day)
+ self.assert_eq(kidx.hour, pidx.hour)
+ self.assert_eq(kidx.minute, pidx.minute)
+ self.assert_eq(kidx.second, pidx.second)
+ self.assert_eq(kidx.microsecond, pidx.microsecond)
+ self.assert_eq(kidx.week, pidx.week)
+ self.assert_eq(kidx.weekofyear, pidx.weekofyear)
+ self.assert_eq(kidx.dayofweek, pidx.dayofweek)
+ self.assert_eq(kidx.weekday, pidx.weekday)
+ self.assert_eq(kidx.dayofyear, pidx.dayofyear)
+ self.assert_eq(kidx.quarter, pidx.quarter)
+ self.assert_eq(kidx.daysinmonth, pidx.daysinmonth)
+ self.assert_eq(kidx.days_in_month, pidx.days_in_month)
+ self.assert_eq(kidx.is_month_start, pd.Index(pidx.is_month_start))
+ self.assert_eq(kidx.is_month_end, pd.Index(pidx.is_month_end))
+ self.assert_eq(kidx.is_quarter_start, pd.Index(pidx.is_quarter_start))
+ self.assert_eq(kidx.is_quarter_end, pd.Index(pidx.is_quarter_end))
+ self.assert_eq(kidx.is_year_start, pd.Index(pidx.is_year_start))
+ self.assert_eq(kidx.is_year_end, pd.Index(pidx.is_year_end))
+ self.assert_eq(kidx.is_leap_year, pd.Index(pidx.is_leap_year))
+
+ if LooseVersion(pd.__version__) >= LooseVersion("1.2.0"):
+ self.assert_eq(kidx.day_of_year, pidx.day_of_year)
+ self.assert_eq(kidx.day_of_week, pidx.day_of_week)
+
+ def test_ceil(self):
+ for kidx, pidx in self.idx_pairs:
+ for freq in self.fixed_freqs:
+ self.assert_eq(kidx.ceil(freq), pidx.ceil(freq))
+
+ self._disallow_nanoseconds(self.kidxs[0].ceil)
+
+ def test_floor(self):
+ for kidx, pidx in self.idx_pairs:
+ for freq in self.fixed_freqs:
+ self.assert_eq(kidx.floor(freq), pidx.floor(freq))
+
+ self._disallow_nanoseconds(self.kidxs[0].floor)
+
+ def test_round(self):
+ for kidx, pidx in self.idx_pairs:
+ for freq in self.fixed_freqs:
+ self.assert_eq(kidx.round(freq), pidx.round(freq))
+
+ self._disallow_nanoseconds(self.kidxs[0].round)
+
+ def test_day_name(self):
+ for kidx, pidx in self.idx_pairs:
+ self.assert_eq(kidx.day_name(), pidx.day_name())
+
+ def test_month_name(self):
+ for kidx, pidx in self.idx_pairs:
+ self.assert_eq(kidx.day_name(), pidx.day_name())
+
+ def test_normalize(self):
+ for kidx, pidx in self.idx_pairs:
+ self.assert_eq(kidx.normalize(), pidx.normalize())
+
+ def test_strftime(self):
+ for kidx, pidx in self.idx_pairs:
+ self.assert_eq(
+ kidx.strftime(date_format="%B %d, %Y"), pidx.strftime(date_format="%B %d, %Y")
+ )
+
+ def test_indexer_between_time(self):
+ for kidx, pidx in self.idx_pairs:
+ self.assert_eq(
+ kidx.indexer_between_time("00:00:00", "00:01:00").sort_values(),
+ pd.Index(pidx.indexer_between_time("00:00:00", "00:01:00")),
+ )
+
+ self.assert_eq(
+ kidx.indexer_between_time(
+ datetime.time(0, 0, 0), datetime.time(0, 1, 0)
+ ).sort_values(),
+ pd.Index(pidx.indexer_between_time(datetime.time(0, 0, 0), datetime.time(0, 1, 0))),
+ )
+
+ self.assert_eq(
+ kidx.indexer_between_time("00:00:00", "00:01:00", True, False).sort_values(),
+ pd.Index(pidx.indexer_between_time("00:00:00", "00:01:00", True, False)),
+ )
+
+ self.assert_eq(
+ kidx.indexer_between_time("00:00:00", "00:01:00", False, True).sort_values(),
+ pd.Index(pidx.indexer_between_time("00:00:00", "00:01:00", False, True)),
+ )
+
+ self.assert_eq(
+ kidx.indexer_between_time("00:00:00", "00:01:00", False, False).sort_values(),
+ pd.Index(pidx.indexer_between_time("00:00:00", "00:01:00", False, False)),
+ )
+
+ self.assert_eq(
+ kidx.indexer_between_time("00:00:00", "00:01:00", False, False).sort_values(),
+ pd.Index(pidx.indexer_between_time("00:00:00", "00:01:00", False, False)),
+ )
Review comment:
It's updated. Good catch!
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