pyfixedwidths 0.1.0

Easy way converting from text, list, or dict to text or list with fixed widths.

Easy way converting from text, list, or dict to text or list with fixed widths.

The Installation

>>> pip install pyfixedwidths

Examples

>>> from pyfixedwidths import FixedWidthFormatter
>>> text = (
>>> "1,2,3,4\n"
>>> "11,,33,44\n"
>>> )
>>>
>>> listofdict = [
>>>     dict(name="John Doe", age=20, hobby="swim"),
>>>     dict(name="John Smith", age=100, job="teacher"),
>>> ]
>>>
>>> array = [
>>>     [1, None, 3, 4],
>>>     [11, 22, None, 44],
>>> ]
>>>

>>> fw = FixedWidthFormatter()
>>> fw.from_text(text).to_text(padding=1)
>>> #=>
>>>     ("1  , 2 , 3  , 4 \n"
>>>      "11 ,   , 33 , 44\n")
>>>
>>> fw.from_text(text).to_array(padding=1)
>>> #=>
>>>     [["1  "," 2 "," 3  "," 4 "],
>>>      ["11 ","   "," 33 "," 44"],]
>>>

>>> fw = FixedWidthFormatter()
>>> fw.from_array(array).to_text(padding=0)
>>> #=>
>>>     ("1 ,None,3   ,4 \n"
>>>      "11,    ,None,44\n")
>>>
>>> fw.from_array(array).to_array(padding=0)
>>> #=>
>>>     [["1 ","None","3   ","4 "],
>>>      ["11","    ","None","44"],]
>>>

>>> fw = FixedWidthFormatter(schema=schema)
>>> fw.from_dict(listofdict).to_text(padding=0)
>>> #=>
>>>     ("name      ,age,hobby,job    \n"
>>>      "John Doe  ,20 ,swim ,       \n"
>>>      "John Smith,100,     ,teacher\n")
>>>
>>> fw.from_dict(listofdict).to_list(padding=0)
>>> #=>
>>>     [["name      ", "age", "hobby", "job    "],
>>>      ["John Doe  ", "20 ", "swim ", "       "],
>>>      ["John Smith", "100", "     ", "teacher"],]

>>> schema = [
>>>     dict(
>>>         justification="rjust"
>>>     ),
>>>     dict(
>>>         format=":>5s"
>>>     ),
>>>     dict(),
>>>     dict(
>>>         format=":2s"
>>>     )
>>> ]
>>>
>>> fw = FixedWidthFormatter(schema=schema)
>>> fw.from_dict(listofdict).to_text(padding=2)
>>> #=>
>>>     ("      name  ,    age  ,  hobby  ,  job\n"
>>>      "  John Doe  ,     20  ,  swim   ,    \n"
>>>      "John Smith  ,    100  ,         ,  teacher\n")
>>>
>>> fw.from_dict(listofdict, headers=["hobby", "job", "location", "name"]).to_text(padding=1)
>>> #=>
>>>     (   "hobby ,     job , location , name\n"
>>>         " swim ,         ,          , John Doe\n"
>>>         "      , teacher ,          , John Smith\n")

Requirements

• Python 3