test_timestamp:test_class_ops_pytz can fail due to bad luck of timing of calls
#### Code Sample, a copy-pastable example if possible

I had a test fail in CI and the output looks like this:

```
______________________ TestTimestamp.test_class_ops_pytz _______________________
[gw1] linux -- Python 3.6.6 /home/travis/miniconda3/envs/pandas-dev/bin/python

self = <pandas.tests.scalar.timestamp.test_timestamp.TestTimestamp object at 0x7fb560287320>

    def test_class_ops_pytz(self):
        def compare(x, y):
            assert int(Timestamp(x).value / 1e9) == int(Timestamp(y).value / 1e9)
    
        compare(Timestamp.now(), datetime.now())
        compare(Timestamp.now("UTC"), datetime.now(timezone("UTC")))
        compare(Timestamp.utcnow(), datetime.utcnow())
>       compare(Timestamp.today(), datetime.today())

pandas/tests/scalar/timestamp/test_timestamp.py:759: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

x = Timestamp('2020-01-21 03:19:15.998086')
y = datetime.datetime(2020, 1, 21, 3, 19, 16, 5328)

    def compare(x, y):
>       assert int(Timestamp(x).value / 1e9) == int(Timestamp(y).value / 1e9)
E       AssertionError: assert 1579576755 == 1579576756
E        +  where 1579576755 = int((1579576755998086000 / 1000000000.0))
E        +    where 1579576755998086000 = Timestamp('2020-01-21 03:19:15.998086').value
E        +      where Timestamp('2020-01-21 03:19:15.998086') = Timestamp(Timestamp('2020-01-21 03:19:15.998086'))
E        +  and   1579576756 = int((1579576756005328000 / 1000000000.0))
E        +    where 1579576756005328000 = Timestamp('2020-01-21 03:19:16.005328').value
E        +      where Timestamp('2020-01-21 03:19:16.005328') = Timestamp(datetime.datetime(2020, 1, 21, 3, 19, 16, 5328))
```



#### Problem description

So due to "bad luck", the call to `Timestamp.today()` was just before the next second that hit when `datetime.now()` was called, making the comparison fail.  I think the comparison should be:

```
int((Timestamp(x).value - Timestamp(y).value)/1.0e9) == 0
```
which would handle this round off error better.

#### Expected Output

No failure

#### Output of ``pd.show_versions()``

<details>

>>> pd.show_versions()                                                          
C:\Anaconda3\envs\pandas-dev\lib\site-packages\fastparquet\dataframe.py:5: Futur
eWarning: pandas.core.index is deprecated and will be removed in a future versio
n.  The public classes are available in the top-level namespace.                
  from pandas.core.index import CategoricalIndex, RangeIndex, Index, MultiIndex 
                                                                                
INSTALLED VERSIONS                                                              
------------------                                                              
commit           : 8e4dfff71a0547c821e67477b65c7b1930df588e                     
python           : 3.7.6.final.0                                                
python-bits      : 64                                                           
OS               : Windows                                                      
OS-release       : 10                                                           
machine          : AMD64                                                        
processor        : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel         
byteorder        : little                                                       
LC_ALL           : None                                                         
LANG             : None                                                         
LOCALE           : None.None                                                    
                                                                                
pandas           : 1.0.0rc0+156.g8e4dfff71                                      
numpy            : 1.17.3                                                       
pytz             : 2019.3                                                       
dateutil         : 2.8.1                                                        
pip              : 19.3.1                                                       
setuptools       : 42.0.2.post20191201                                          
Cython           : 0.29.14                                                      
pytest           : 5.3.2                                                        
hypothesis       : 4.57.1                                                       
sphinx           : 2.3.1                                                        
blosc            : None                                                         
feather          : None                                                         
xlsxwriter       : 1.2.7                                                        
lxml.etree       : 4.4.2                                                        
html5lib         : 1.0.1                                                        
pymysql          : None                                                         
psycopg2         : None                                                         
jinja2           : 2.10.3                                                       
IPython          : 7.10.1                                                       
pandas_datareader: None                                                         
bs4              : 4.8.2                                                        
bottleneck       : 1.3.1                                                        
fastparquet      : 0.3.2                                                        
gcsfs            : None                                                         
lxml.etree       : 4.4.2                                                        
matplotlib       : 3.1.2                                                        
numexpr          : 2.7.0                                                        
odfpy            : None                                                         
openpyxl         : 3.0.1                                                        
pandas_gbq       : None                                                         
pyarrow          : 0.15.1                                                       
pytables         : None                                                         
pytest           : 5.3.2                                                        
pyxlsb           : None                                                         
s3fs             : 0.4.0                                                        
scipy            : 1.3.1                                                        
sqlalchemy       : 1.3.12                                                       
tables           : 3.6.1                                                        
tabulate         : 0.8.6                                                        
xarray           : 0.14.1                                                       
xlrd             : 1.2.0                                                        
xlwt             : 1.3.0                                                        
xlsxwriter       : 1.2.7                                                        
numba            : 0.46.0                                                       
>>>                                                                             
</details>
