Resolving conflicts

There is currently no in-built support for resolving conflicts within a table using petl, however this notebook gives an example of a workaround strategy.

import sys
sys.version_info

sys.version_info(major=3, minor=4, micro=2, releaselevel='final', serial=0)

import petl as etl
etl.__version__

'1.0.6'

data_master = b"""id  name              value            age
 1  Tressa           1203              42
 2  Phil                23997            
 3  Darius                .                 78
 4  Delinda          96501            64
 5  Adelina          96508             50
"""
tbl_master = (
    etl
    .fromtext(etl.MemorySource(data_master))
    .split('lines', r'\s+')
    .skip(1)
    .replaceall('.', None)
    .addfield('master_age', lambda row: row.age)
)
tbl_master

id	name	value	age	master_age
1	Tressa	1203	42	42
2	Phil	23997	None	None
3	Darius	None	78	78
4	Delinda	96501	64	64
5	Adelina	96508	50	50

data_other = b"""id  name                value            age
 2  Phil                 .                    53
 3  Darius           5000             76
"""
tbl_other = (
    etl
    .fromtext(etl.MemorySource(data_other))
    .split('lines', r'\s+')
    .skip(1)
    .replaceall('.', None)
)
tbl_other

id	name	value	age
2	Phil	None	53
3	Darius	5000	76

tbl_merge = etl.merge(tbl_master, tbl_other, key='id')
tbl_merge

id	name	value	age	master_age
1	Tressa	1203	42	42
2	Phil	23997	53	None
3	Darius	5000	Conflict({'76', '78'})	78
4	Delinda	96501	64	64
5	Adelina	96508	50	50

tbl_merge_resolved = (
    tbl_merge
    .convert('age', lambda v, row: (row.master_age if isinstance(v, etl.Conflict) else v),
             pass_row=True)
    .cutout('master_age')
)
tbl_merge_resolved

id	name	value	age
1	Tressa	1203	42
2	Phil	23997	53
3	Darius	5000	78
4	Delinda	96501	64
5	Adelina	96508	50