textdata 2.4.1

Easily get clean data, direct from text or Python source

One often needs to state data in program source. Python, however, needs its program lines indented just so. Multi-line strings therefore often have extra spaces and newline characters you didn’t really want. Many developers “fix” this by using Python list literals, but that’s tedious, verbose, and often less legible.

The textdata package makes it easy to have clean, nicely-whitespaced data specified in your program, but to get the data without extra syntax cluttering things up. It’s permissive of the layouts needed to make Python code look and work right, without reflecting those requirements in the resulting data.

Text (Strings and Lists)

>>> lines("""
...     There was an old woman who lived in a shoe.
...     She had so many children, she didn't know what to do;
...     She gave them some broth without any bread;
...     Then whipped them all soundly and put them to bed.
... """)
['There was an old woman who lived in a shoe.',
 "She had so many children, she didn't know what to do;",
 'She gave them some broth without any bread;',
 'Then whipped them all soundly and put them to bed.']

Note that the “extra” newlines and leading spaces have been taken care of and discarded. Or do you want that as just one string? Okay:

>>> text("""
...     There was an old woman who lived in a shoe.
...     She had so many children, she didn't know what to do;
...     She gave them some broth without any bread;
...     Then whipped them all soundly and put them to bed.
... """)
"There was an old woman who lived in a shoe.\nShe ...put them to bed."

Here text() does the same stripping of pointless whitespace at the beginning and end of lines, returning the data as a clean, convenient string. Or if you don’t want most of the line endings, try textline on the same input to get a single no-breaks line.

Words and Phrases

Other times, the data you need is almost, but not quite, a series of words. A list of names, a list of colors–values that are mostly single words, but sometimes have an embedded spaces. textdata has you covered:

>>> words(' Billy Bobby "Mr. Smith" "Mrs. Jones"  ')
['Billy', 'Bobby', 'Mr. Smith', 'Mrs. Jones']

Embedded quotes (either single or double) can be used to construct “words” (or phrases) containing whitespace (including tabs and newlines).

words, like the other textdata facilities, allows you to comment individual lines that would otherwise muck up string literals:

exclude = words("""
    __pycache__ *.pyc *.pyo     # compilation artifacts
    .hg* .git*                  # repository artifacts
    .coverage                   # code tool artifacts
    .DS_Store                   # platform artifacts
""")

Yields:

['__pycache__', '*.pyc', '*.pyo', '.hg*', '.git*',
 '.coverage', '.DS_Store']

Paragraphs

Instead of words, you might wan to collect “paragraphs”–contiguous runs of text lines delineated by blank lines. Markdown and RST document formats, for example, use this convention.

>>> rhyme = """
    Hey diddle diddle,

    The cat and the fiddle,
    The cow jumped over the moon.
    The little dog laughed,
    To see such sport,

    And the dish ran away with the spoon.
"""
>>> paras(rhyme)
[['Hey diddle diddle,'],
 ['The cat and the fiddle,',
  'The cow jumped over the moon.',
  'The little dog laughed,',
  'To see such sport,'],
 ['And the dish ran away with the spoon.']]

Or if you’d like paras, but each paragraph in a single string:

>>> paras(rhyme, join="\n")
['Hey diddle diddle,',
 'The cat and the fiddle,\nThe cow jumped over the moon.\nThe little dog laughed,\nTo see such sport,',
 'And the dish ran away with the spoon.']

Dictionaries

Or maybe you want a dict. The attrs function makes it easy to grab:

.. code-block:: pycon

>>> attrs("a=1 b=2 c='something more'")
{'a': 1, 'b': 2, 'c': 'something more'}

If you want to cut and paste data directly from JavaScript, JSON, HTML, CSS, or XML, easy peasy! No text editing required.

>>> # JavaScript
>>> attrs("a: 1, b: 2, c: 'something more'")
{'a': 1, 'b': 2, 'c': 'something more'}

>>> # JSON
>>> attrs('"a": 1, "b": 2, "c": "something more"')
{'a': 1, 'b': 2, 'c': 'something more'}

>>> # HTML or XML
>>> attrs('a="1" b="2" c="something more"')
{'a': '1', 'b': '2', 'c': 'something more'}

>>> # above returns strings, because values quoted, which denotes strings
>>> # 'full' evaluation needed to transform strings into values
>>> attrs('a="1" b="2" c="something more"', evaluate='full')
{'a': 1, 'b': 2, 'c': 'something more'}

>>> # CSS
>>> attrs("a: 1; b: 2; c: 'something more'")
{'a': 1, 'b': 2, 'c': 'something more'}

Tables

Or maybe you have tabular data.

>>> tabledata = """
...     name  age  strengths
...     ----  ---  ---------------
...     Joe   12   woodworking
...     Jill  12   slingshot
...     Meg   13   snark, snapchat
... """

>>> table(tabledata)
[['name', 'age', 'strengths'],
 ['Joe', 12, 'woodworking'],
 ['Jill', 12, 'slingshot'],
 ['Meg', 13, 'snark, snapchat']]

>>> records(tabledata)
[{'name': 'Joe', 'age': 12, 'strengths': 'woodworking'},
 {'name': 'Jill', 'age': 12, 'strengths': 'slingshot'},
 {'name': 'Meg', 'age': 13, 'strengths': 'snark, snapchat'}]

This works even if you have a table with a lot of extra fluff:

>>> fancy = """
... +------+-----+-----------------+
... | name | age | strengths       |
... +------+-----+-----------------+
... | Joe  |  12 | woodworking     |
... | Jill |  12 | slingshot       |
... | Meg  |  13 | snark, snapchat |
... +------+-----+-----------------+
... """
>>> assert table(tabledata) == table(fancy)
>>> assert records(tabledata) == records(fancy)

It works with tables formatted in a variety of ways including Markdown, RST, ANSI/Unicode line drawing characters, plain text columns and borders…. You’d might think table parsing would be a dicey proposition, prone to failure, but textdata has dozens of tests, including rather complex cases, showing it’s a reliable, high-probability heuristic.

In Summary

textdata is all about conveniently grabbing the data you want from text files and program source, and doing it in a highly functional, convenient, well-tested way. Take it for a spin today!

See the full documentation at Read the Docs.