In case you want more details about the differences, you could also use
difflib...
from difflib import SequenceMatcher
seq1 = [tuple(row.values()) for row in resultproxy1]
seq2 = [tuple(row.values()) for row in resultproxy2]
sm = SequenceMatcher(a=seq1, b=seq2, autojunk=False)
print(sm.get_opcodes())
print(f'similarity: {sm.ratio()}')
assert sm.ratio() == 1 # example to ensure results are equivalent
assert sm.ratio() == 1, sm.get_opcodes() # pytest syntax to show the
opcodes if the assertion fails
Steven James
On Friday, 29 November 2019 09:13:23 UTC-5, sumau wrote:
>
> Hello
>
> I think my original question was too generic so rephrasing... Is there a
> way in sqlalchemy to:
>
> 1. Assert a ResultProxy against an expected ResultProxy (or list of
> RowProxies against expected list of RowProxies)
> 2. Show any differences
>
> I wanted to check first before writing my own script :-)
>
> Regards
> S
>
> On Friday, 22 November 2019 10:50:54 UTC, sumau wrote:
>>
>> Hello
>>
>> I would like to assert the contents of tables in my PG schema i.e. make
>> sure it contains the data I'm expecting
>>
>> I am aware of various options:
>>
>> 1) Compare the actual and expected tables using a sql query, orchestrated
>> by sqlalchemy (i.e. create the actual and expected tables in DB, run the
>> sql comparison script, return the output)
>> 2) Load the actual tables as tuples and compare them with expected tuples
>> using something like assert_result
>>
>> https://github.com/sqlalchemy/sqlalchemy/blob/d933ddd503a1ca0a7c562c51c503139c541e707e/lib/sqlalchemy/testing/assertions.py#L465
>> 3) Load the actual tables as dataframes and compare them with expected
>> dataframes using pandas assert_frame_equal
>>
>> https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.testing.assert_frame_equal.html
>>
>> Any recommendations / thoughts would be much appreciated, both as to the
>> approach and the implementation :-)
>>
>
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