8.5. Has Parsers¶

8.5.1. Has¶

Getting Started¶

Lets import our easydata module first.

>>> import easydata as ed

Has supports any query object for fetching data.

>>> test_dict = {'info': {'stock': True}}
>>> ed.Has(ed.jp('info.stock')).parse(test_dict)
True

In this case if jp returns None, then bool parser will also return False.

>>> test_dict = {}
>>> ed.Has(ed.jp('invalid-key')).parse(test_dict)
False

Use of query selectors is not required, as we can see bellow.

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Has().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().parse(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Has().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().parse(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Has().parse(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Has().parse(test_data)
True

>>> test_data = True
>>> ed.Has().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().parse(test_data)
True

>>> test_data = True
>>> ed.Has().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().parse(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().transform(test_data)
True

>>> test_data = True
>>> ed.Bool().parse(test_data)
True

Parameters¶

contains¶

contains property can accept list of keys which will be used for a match in a lookup text. If match is found then True is returned. Please note that search keys are not case sensitive and regex pattern as a key is also accepted.

>>> text = 'Easybook Pro 13'
>>> ed.Has(contains=['pro 13']).parse(text)
True

ccontains¶

ccontains works in a same way as contains parameter, with an exception that keys are case sensitive.

>>> text = 'Easybook Pro 13'
>>> ed.Has(contains=['Pro 13']).parse(text)
True

Lets try with lowercase keys.

>>> text = 'Easybook Pro 13'
>>> ed.Has(contains=['Pro 13']).parse(text)
False

contains_query¶

contains_query is a powerful feature that enables you to specify dynamic search keys by using query selectors. In example bellow we will use jp query selector to get our contains keys.

>>> test_dict = {'title': 'Easybook Pro 13', 'info': {'brand': 'Easybook}'}
>>> ed.Has(ed.jp('title'), contains_query=ed.jp('info.brand')).parse(text)
True

contains_query_source¶

contains_query_source will work only when our bool parser is used inside model in order to select different source from data object.

import easydata as ed

class ProductItemModel(ed.ItemModel):
    item_stock = parsers.Has(
        ed.jp('title'),
        contains_query=ed.jp('name')
        contains_query_source='brand_data'
    )

Now lets test our newly created model with adding multiple data sources to it.

>>> test_dict = {'title': 'Easybook Pro 13'}
>>> test_brand_dict = {'name': 'Easybook'}
>>> item_model = ProductItemModel().parse(test_dict, brand_data=test_brand_dict)
{'stock': True}

empty_as_false¶

By default bool parser will always return False if there is no match or if given lookup data is empty or contains value of None.

If you need to disable default behaviour and return empty data if given lookup data is empty, you have to set parameter empty_as_false to False.

Lets see in example bellow first how default behaviour works.

>>> test_dict = None
>>> ed.Has(ed.jp('info.stock')).parse(test_dict)
False

Lets set empty_as_false to False and see what it returns.

>>> test_dict = None
>>> ed.Has(ed.jp('info.stock'), empty_as_false=False).parse(test_dict)
None