mirror of https://github.com/python/cpython
Better re.split examples.
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@ -1091,16 +1091,21 @@ method is invaluable for converting textual data into data structures that can b
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easily read and modified by Python as demonstrated in the following example that
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creates a phonebook.
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First, get the input using triple-quoted string syntax::
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First, here is the input. Normally it may come from a file, here we are using
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triple-quoted string syntax::
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>>> input = """Ross McFluff 834.345.1254 155 Elm Street
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Ronald Heathmore 892.345.3428 436 Finley Avenue
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Frank Burger 925.541.7625 662 South Dogwood Way
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Heather Albrecht 548.326.4584 919 Park Place"""
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>>> input = """Ross McFluff: 834.345.1254 155 Elm Street
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Then, convert the string into a list with each line having its own entry::
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Ronald Heathmore: 892.345.3428 436 Finley Avenue
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Frank Burger: 925.541.7625 662 South Dogwood Way
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>>> entries = re.split("\n", input)
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Heather Albrecht: 548.326.4584 919 Park Place"""
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The entries are separated by one or more newlines. Now we convert the string
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into a list with each nonempty line having its own entry::
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>>> entries = re.split("\n+", input)
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>>> entries
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['Ross McFluff 834.345.1254 155 Elm Street',
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'Ronald Heathmore 892.345.3428 436 Finley Avenue',
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@ -1111,16 +1116,17 @@ Finally, split each entry into a list with first name, last name, telephone
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number, and address. We use the ``maxsplit`` paramater of :func:`split`
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because the address has spaces, our splitting pattern, in it::
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>>> [re.split(" ", entry, 3) for entry in entries]
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>>> [re.split(":? ", entry, 3) for entry in entries]
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[['Ross', 'McFluff', '834.345.1254', '155 Elm Street'],
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['Ronald', 'Heathmore', '892.345.3428', '436 Finley Avenue'],
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['Frank', 'Burger', '925.541.7625', '662 South Dogwood Way'],
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['Heather', 'Albrecht', '548.326.4584', '919 Park Place']]
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With a ``maxsplit`` of ``4``, we could seperate the house number from the street
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name::
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The ``:?`` pattern matches the colon after the last name, so that it does not
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occur in the result list. With a ``maxsplit`` of ``4``, we could seperate the
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house number from the street name::
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>>> [re.split(" ", entry, 4) for entry in entries]
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>>> [re.split(":? ", entry, 4) for entry in entries]
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[['Ross', 'McFluff', '834.345.1254', '155', 'Elm Street'],
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['Ronald', 'Heathmore', '892.345.3428', '436', 'Finley Avenue'],
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['Frank', 'Burger', '925.541.7625', '662', 'South Dogwood Way'],
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