added the query_filter parameter in which a filter on a table's data can be applied, inspired by pandas.query
for example, the line client.get('Pets', query_filter='name == jerry') returns a csv file with the rows that match the column 'name' being equal to the value 'jerry'
Filters to implement:
[x] col_1 == str_val_1
[x] col_1 == str_val_1 and col_2 == str_val_2
[ ] col_1 == str_val_1 or col_2 == str_val_2
[ ] col_1 == int_val
[ ] col_1 == float_val
[ ] col_1 == ref.name
[ ] col_1 == str_val and col_2 <= int_val
[ ] col_1 > float_val_1 and col_1 < float_val_2
how to test:
explain here what to do to test this (or point to unit tests)
todo:
[ ] updated docs in case of new feature
[ ] added/updated tests
[ ] added/updated testplan to include a test for this fix, including ref to bug using # notation
What are the main changes you did:
query_filter
parameter in which a filter on a table's data can be applied, inspired by pandas.queryclient.get('Pets', query_filter='name == jerry')
returns a csv file with the rows that match the column 'name' being equal to the value 'jerry'Filters to implement:
col_1 == str_val_1
col_1 == str_val_1 and col_2 == str_val_2
col_1 == str_val_1 or col_2 == str_val_2
col_1 == int_val
col_1 == float_val
col_1 == ref.name
col_1 == str_val and col_2 <= int_val
col_1 > float_val_1 and col_1 < float_val_2
how to test:
todo: