python-dif

Navy Data Interchange Format module. Filling a hole in your life.

http://en.wikipedia.org/wiki/Data_Interchange_Format

Reader classes work fine. Writer classes not written yet.

Usage

Depending on reader class DataInterchangeFormat can represent data in several different ways:

as a list of tuples

>>> import DataInterchangeFormat
>>> dif = DataInterchangeFormat.DIFReader("./tests/test.dif", first_row_keys=True)
>>> dif.sheet
[
	[
		('boolean', True),
		('text', 'psychic'),
		('numeric', 1),
		('errors', 'ERROR'),
		('dates', '10/25/2013 19:21:51')
	],
	[
		('boolean', False),
		('text', 'powerless'),
		('numeric', 0.1),
		('errors', 'ERROR'),
		('dates', 'Fri Oct 25 15:31:08 2013')],
	[
		('boolean', ''),
		('text', 'another'),
		('numeric', 1000),
		('errors', ''),
		('dates', 1382729606.27435)
	] ...

]

as a list of dictionaries

>>> dif = DataInterchangeFormat.DIFDictReader("./tests/test.dif", first_row_keys=True)
>>> dif.sheet
[
	{
		'text': 'psychic',
		'dates': '10/25/2013 19:21:51',
		'boolean': True,
		'errors': 'ERROR',
		'numeric': 1
	},
	{
		'text': 'powerless',
		'dates': 'Fri Oct 25 15:31:08 2013',
		'boolean': False,
		'errors': 'ERROR',
		'numeric': 0.1
	},
	{
		'text': 'another',
		'dates': 1382729606.27435,
		'boolean': '',
		'errors': '',
		'numeric': 1000
	} ...
]

as a list of objects

Each row object contains row data in tuple, dict and list formats. List format has no header information and is accessed via index like tuples.

>>> dif = DataInterchangeFormat.DIFObjReader("./tests/test.dif", first_row_keys=True)
>>> dif.sheet
[
	<DataInterchangeFormat.Row object at 0x1c7aa50>,
	<DataInterchangeFormat.Row object at 0x1c7a9d0>,
	<DataInterchangeFormat.Row object at 0x1c7a890> ...
]

>>> dif.sheet[0].list
[True, 'psychic', 1, 'ERROR', '10/25/2013 19:21:51']

>>> dif.sheet[0].dict
{'text': 'psychic', 'dates': '10/25/2013 19:21:51', 'boolean': True, 'errors': 'ERROR', 'numeric': 1}

>>> dif.sheet[0].tuple
[('boolean', True), ('text', 'psychic'), ('numeric', 1), ('errors', 'ERROR'), ('dates', '10/25/2013 19:21:51')]

Input

Reader classes can accept a string, a file path or a file-like object as input.

as a file path

dif = DataInterchangeFormat.DIFReader("./test.dif", first_row_keys=True)

as an open file

with open("./test.dif", "r") as f:
	dif = DataInterchangeFormat.DIFReader(f, first_row_keys=True)

as a string

with open("./test.dif", "r") as f:
	dif = DataInterchangeFormat.DIFReader(f.read(), first_row_keys=True)

"Header" Row

To use your first row as keys, invoke with first_row_keys=True. Invoking without first_row_keys will result in keys being named for the column index.

# generate keys from index
>>> import DataInterchangeFormat
>>> dif = DataInterchangeFormat.DIFObjReader("./tests/test.dif")
>>> dif.sheet[1].tuple
[('col0', True), ('col1', 'psychic'), ('col2', 1), ('col3', 'ERROR'), ('col4', '10/25/2013 19:21:51')]
# with first row as keys
>>> dif_hdr = DataInterchangeFormat.DIFObjReader("./tests/test.dif", first_row_keys=True)
>>> dif_hdr.sheet[0].tuple
[('boolean', True), ('text', 'psychic'), ('numeric', 1), ('errors', 'ERROR'), ('dates', '10/25/2013 19:21:51')]

DateTime Columns

If you have python-dateutils installed (http://labix.org/python-dateutil), supply a list of columns that have date/time values to self.parseDates.

>>> import DataInterchangeFormat
>>> dif = DataInterchangeFormat.DIFObjReader("./tests/test.dif", first_row_keys=True)
>>> dif.sheet[0].dict
{'text': 'psychic', 'dates': '10/25/2013 19:21:51', 'boolean': True, 'errors': 'ERROR', 'numeric': 1}
>>> dif.parseDates(["dates"])
>>> dif.sheet[0].dict
{'text': 'psychic', 'dates': datetime.datetime(2013, 10, 25, 19, 21, 51), 'boolean': True, 'errors': 'ERROR', 'numeric': 1}