It appears that the following assertion works assuming that result set can
be = 0 (no data) or > 0 there is data
assert df2.count() >= 0
However, if I wanted to write to a JDBC database from PySpark through a
function (already defined in another module) as below
def writeTableToOracle(dataFrame,mode,dataset,tableName):
try:
dataFrame. \
write. \
format("jdbc"). \
option("url", oracle_url). \
option("dbtable", tableName). \
option("user", config['OracleVariables']['oracle_user']). \
option("password",
config['OracleVariables']['oracle_password']). \
option("driver", config['OracleVariables']['oracle_driver']). \
mode(mode). \
save()
except Exception as e:
print(f"""{e}, quitting""")
sys.exit(1)
and call it in the program
from sparkutils import sparkstuff as s
s.writeTableToOracle(df2,"overwrite",config['OracleVariables']['dbschema'],config['OracleVariables']['yearlyAveragePricesAllTable'])
How can one assert its validity in PyTest?
Thanks again
On Wed, 3 Feb 2021 at 15:12, Mich Talebzadeh <[email protected]>
wrote:
> Hi,
>
> In Pytest you want to ensure that the composed DF has the correct return.
>
> Example
>
> df2 = house_df. \
> select( \
> F.date_format('datetaken', 'yyyy').cast("Integer").alias('YEAR') \
> , 'REGIONNAME' \
> ,
> round(F.avg('averageprice').over(wSpecY)).alias('AVGPRICEPERYEAR') \
> ,
> round(F.avg('flatprice').over(wSpecY)).alias('AVGFLATPRICEPERYEAR') \
> ,
> round(F.avg('TerracedPrice').over(wSpecY)).alias('AVGTERRACEDPRICEPERYEAR')
> \
> ,
> round(F.avg('SemiDetachedPrice').over(wSpecY)).alias('AVGSDPRICEPRICEPERYEAR')
> \
> ,
> round(F.avg('DetachedPrice').over(wSpecY)).alias('AVGDETACHEDPRICEPERYEAR')).
> \
> distinct().orderBy('datetaken', asending=True)
>
> Will that be enough to run just this command
>
> assert not []
>
> I believe that may be flawed because any error will be assumed to be NOT
> NULL?
>
> Thanks
>
>
>
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