Seeding and Custom Randomization

Seeding

If you want to test and produce consistent results, you can use the seed option:

In [79]: SG("[\w]{10}&[\d]{10}", seed=4318).render_list(10)
Out[79]:
['42U1uqGt5qG0519J6562',
 'q5d68X3n66r5h81pdz59',
 '1u307GH7Ad9Xmd1Zg119',
 'I7R224u5efft78A6986h',
 '3TP43404okw7Q5R019l4',
 '0D3952i05QYe1C935y36',
 '219W9iw9924XYy368E4B',
 '5F74c59Sy947LNw28p86',
 'W3ocGxWw675166352862',
 '35A6G69rEjh4U58t9X5E']

In [80]: SG("[\w]{10}&[\d]{10}", seed=4318).render_list(10)
Out[80]:
['42U1uqGt5qG0519J6562',
 'q5d68X3n66r5h81pdz59',
 '1u307GH7Ad9Xmd1Zg119',
 'I7R224u5efft78A6986h',
 '3TP43404okw7Q5R019l4',
 '0D3952i05QYe1C935y36',
 '219W9iw9924XYy368E4B',
 '5F74c59Sy947LNw28p86',
 'W3ocGxWw675166352862',
 '35A6G69rEjh4U58t9X5E']

Notice these two lists are exactly the same.

Normally, when the StringGenerator is initialised, it will try to use random.SystemRandom as the random method provider. It falls back gracefully to random.Random if that is not available.

When you use the seed option, it will force use of random.Random and use the provided seed value, which can be any integer. This will cause the results to be the same each time you initialise the StringGenerator.

Custom Random Class

You can also provide your own Random class. Currently we use these methods:

• choice()

• randint()

• shuffle()

So, you’d need to provide at least these with the same arguments and return types as Random and SystemRandom.

See documentation for the Python Standard Library random package

BEWARE: you should provide all the methods of `Random()` in your custom class because we might change the implementation of StringGenerator to use different methods.