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No, I've not had my article hijacked by a Lorem ipsum generator. For this month's Nooks & Crannies column, I found an interesting little Python library to help developers generate random data for their applications. It's called Elizabeth.
Written by Líkið Geimfari, and licensed under the MIT license, Elizabeth has a set of 18 data providers in 21 different locales that you can use to generate random information, including names and personal characteristics, addresses, text data, transportation information, networking and Internet social media data, numbers, and much more. Installation requires Python 3.2 or higher, and you can either install it using pip, or from the git repository.
For my test drive, I installed with pip, on a fresh Debian Jessie box. You'll need to apt-get install python3-pip, which will install Python and needed dependencies. Then pip install elizabeth, and you're ready to use it.
Just for giggles, let's generate some random data on a person in the Python interactive interpreter:
>>> from elizabeth import Personal
>>> p=Personal('en')
>>> p.full_name(gender="male")
'Elvis Herring'
>>> p.blood_type()
'B+'
>>> p.credit_card_expiration_date()
'09/17'
>>> p.email(gender='male')
'jessie7517@gmail.com'
>>> p.favorite_music_genre()
'Ambient'
>>> p.identifier(mask='13064########')
'1306420450944'
>>> p.sexual_orientation()
'Heterosexual'
>>> p.work_experience()
39
>>> p.occupation()
'Senior System Designer'
>>>Using it in your code works just the same way—create an object, and then call the methods you want to fill in your data.
There are 18 different generator tools built into Elizabeth, and adding a new one is not at all difficult; you just have to define the routines that get the data from a JSON collection of values. Here's some random text string generation, again in the interpreter:
>>> from elizabeth import Text
>>> t=Text('en')
>>> t.swear_word()
'Rat-fink'
>>> t.quote()
'Let them eat cake.'
>>> t.words(quantity=20)
['securities', 'keeps', 'accessibility', 'barbara', 'represent', 'hentai', 'flower', 'keys', 'rpm', 'queen', 'kingdom', 'posted', 'wearing', 'attend', 'stack', 'interface', 'quite', 'elementary', 'broadcast', 'holland']
>>> t.sentence()
'She spent her earliest years reading classic literature, and writing poetry.'It's not a difficult exercise to use Elizabeth to populate a SQLite or other database you might need for development or testing. The introductory documentation gives an example for a medical application using the Flask lightweight web framework.
I'm very impressed with Elizabeth—it's super-fast, lightweight, easily extensible, and the community, while small, is active and engaged. As of this writing, there have been 25 committers to the project, and issues are being handled swiftly. The full documentation for Elizabeth is easy to read and follow, and provides an extensive API reference, at least for US English.
I tried tinkering with the links to find if documentation was available in other languages, but I didn't have any success. Because the APIs are different in non-English locales, documenting those variations would be extremely helpful for users. To be fair, it's not terribly hard to read the code and find out what methods are available, even if your Python-fu is not strong. Another glaring lack, for me, was the lack of Arabic or Hebrew locale test data. These are notable right-to-left languages, and for developers who are trying to internationalize their application, proper handling of these languages is a major hurdle. Tools like Elizabeth that can assist with that effort are great to have.
For developers needing sample data for their applications, Elizabeth is a valuable tool, and for those trying to create truly multilingual, localizable applications, it could be a treasure.
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