8000 Added test test_datetimeField_after_setitem for issue #6942 by anirudnits · Pull Request #28790 · pandas-dev/pandas · GitHub
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Added test test_datetimeField_after_setitem for issue #6942 #28790

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Added test test_datetimeField_after_setitem for issue #6942 #28790

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187ad13
Added test test_datetimeField_after_setitem for issue #6942 in test_f…
anirudnits Oct 4, 2019
80c52d6
Added sleep time of 1 second in between assignments
anirudnits Oct 4, 2019
4e02832
Added test test_datetimeField_after_setitem_with_at in tests/generic/…
anirudnits Oct 8, 2019
93f0385
Added test test_datetimeField_after_setitem_with_at in tests/generic/…
anirudnits Oct 8, 2019
259013a
Made the required changes
anirudnits Oct 10, 2019
768d553
Merge branch 'master' of https://github.com/pandas-dev/pandas into ad…
anirudnits Nov 13, 2019
a4db260
Merge branch 'master' of https://github.com/pandas-dev/pandas into ad…
anirudnits Jan 4, 2020
9cbf34c
Fixed a typo which was causing a ValueError
anirudnits Jan 4, 2020
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Added sleep time of 1 second in between assignments
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@anirudnits
anirudnits committed Oct 4, 2019
commit 80c52d60baf534a62de5cad659ee01921b2660e7
5 changes: 5 additions & 0 deletions pandas/tests/generic/test_frame.py
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Expand Up @@ -5,6 +5,7 @@
import numpy as np
import pytest
from datetime import datetime
import time

import pandas.util._test_decorators as td

Expand Down Expand Up @@ -302,13 +303,17 @@ def test_datetimeField_after_setitem(self):
df.at[start, "timenow"] = datetime.today() # initial time.
time1 = df.at[start, "timenow"]

time.sleep(1) # sleep time of 1 second in between assignments.
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These sleep calls are not needed.

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Some tests were failing with AssertionError, so added those.

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Why were AssertionErrors being raised?

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I tried the same code on my computer and got the following results:
time1: 2019-10-04 23:23:31.911241
time2: 2019-10-04 23:23:31.911534
time3: 2019-10-04 23:23:31.912060
that is a time difference of 10^(-3) between the time1 and time2.Now if both the statements are executed within a time frame of <= 10^(-6) then the two will match. So that's why I thought of adding the sleep in between time1, time2 and time3 to ascertain this doesn't happen.

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The tests should generally be

result = pd.DataFrame(index=pd.date_range(start,periods=1), columns=['timenow','Live'])
var = datetime.today()
result.at[start,'timenow'] = var
result.Live = True
expected = pd.DataFrame([[var, True]],index=pd.date_range(start,periods=1), columns=['timenow','Live'])
tm.assert_frame_equal(result, expected)

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Sorry I misread the problem and was writing the test to check if the timenow column changes value after setting the Live column with "at".
So, what the test should check is that the dtype of timenow column remains unchanged after setting the Live column to True with at. For that I could use the assert_series_equal and check the dtype of timenow before and after.
Is that right?

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@mroeschke mroeschke Oct 6, 2019 •
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This test should check that the timenow column changes once df.Live = True

i.e. the example in #6942 (comment) is the fixed behavior that we want to test for.

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Some points:

  1. For the general template of tests that is used in pandas/tests, most of them assert that either two DataFrames or Series are equal and call the predefined functions tm.assert_something_equal. However in this case we assert the column actually changes value and I couldn't find a function for such a case in tm and therefore wrote the individual assert statements for the different values in the timenow column(asserting that they are not equal).

  2. Without the sleep statements inserted, some checks were failing. When I viewed the log of the failed tests I observed that the error was because
    assert not time1 == time2
    was evaluating to
    assert not datetime.datetime(2019, 10, 4, 16, 12, 38, 392372) == datetime.datetime(2019, 10, 4, 16, 12, 38, 392372)
    So I realized that this could only occur if both the statements are run within a time-frame < 10^(-6). When I added the sleep statements the checks passed.

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You will still use tm.assert_frame_equal. You will have to construct the expected dataframe from scratch

In [4]: result = pd.DataFrame(index=pd.date_range(start,periods=1), columns=['timenow','Live'])

In [5]: result.at[start,'timenow'] = datetime.today() # initial value


In [7]: new_date =  datetime.today() 

In [9]: result.Live = True

In [10]: result.at[start,'timenow'] = new_date 

In [11]: expected = pd.DataFrame([[new_date, True]], index=pd.date_range(start,periods=1), columns=['timenow','Live'])

In [12]: tm.assert_frame_equal(result, expected)

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Thanks, couldn't come up with that! Will make the necessary changes and resubmit the PR.


df.at[
start, "timenow"
] = datetime.today() # modified time before 'Live' column is set.
time2 = df.at[start, "timenow"]

df.Live = True # setting the 'Live' column to True.

time.sleep(1) # sleep time of 1 second in between assignments.
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These sleep calls are not needed.

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Some checks were failing with AssertionError, so I added those


df.at[
start, "timenow"
] = datetime.today() # modified time after 'Live' column is set.
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