Field Patterns

Field Patterns Are Optional

We’ve seen what happens if the fuzzytable fields parameter is left blank. All fields whose headers are non-blank are collected by FuzzyTable.

We’ve also seen how passing a list of strings to the fuzzytable fields parameter not only controls which fields are collected, but also what those fields are named, so they can be reliably referenced.

Field Patterns provide another layer of control.

Separate naming from search criteria

Let’s say there’s a field you’d like to name birthday, but the spreadsheet header is called D.O.B. This is where aliases come in.

Let’s say you have this very simple table:

Name	DOB
John Doe	1995
123	2003OCt
Jane Doe	1964
True	2019

# birthdays.py

from fuzzytable import FuzzyTable, FieldPattern

name_field = FieldPattern(
    name="name",
    approximate_match=True,
)

birthday_field = FieldPattern(
    name="birthday",
    alias="DOB",
)

birthday_table = FuzzyTable(
    path='birthdays.csv',
    fields=[name_field, birthday_field],
)

>>> python birthdays.py
>>> for record in birthday_table.records
...     print(record)
...
{'name': 'John Doe', 'birthday': 1995}
{'name': 123, 'birthday': '2003Oct'}
{'name': 'Jane Doe', 'birthday': 1964}
{'name': True, 'birthday': 2019}

Combine FieldPatterns and strings

while the birthday field is declared using the

# birthdays_combined.py

from fuzzytable import FuzzyTable, FieldPattern

birthday_field = FieldPattern(
    name="birthday",
    alias="dob",
)

birthday_table = FuzzyTable(
    path='birthdays.csv',
    fields=['name', birthday_field],  # Mix string literals and FieldPattern objects as desired
    approximate_match=True,
)

This generates the same result as above:

>>> python birthdays_combined.py
>>> for record in birthday_table.records
...     print(record)
...
{'name': 'John Doe', 'birthday': 1995}
{'name': 123, 'birthday': '2003Oct'}
{'name': 'Jane Doe', 'birthday': 1964}
{'name': True, 'birthday': 2019}