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""" Tablib - reStructuredText Support
"""
from itertools import zip_longest
from statistics import median
from textwrap import TextWrapper
JUSTIFY_LEFT = 'left'
JUSTIFY_CENTER = 'center'
JUSTIFY_RIGHT = 'right'
JUSTIFY_VALUES = (JUSTIFY_LEFT, JUSTIFY_CENTER, JUSTIFY_RIGHT)
def to_str(value):
if isinstance(value, bytes):
return value.decode('utf-8')
return str(value)
def _max_word_len(text):
"""
Return the length of the longest word in `text`.
>>> _max_word_len('Python Module for Tabular Datasets')
8
"""
return max(len(word) for word in text.split()) if text else 0
class ReSTFormat:
title = 'rst'
extensions = ('rst',)
MAX_TABLE_WIDTH = 80 # Roughly. It may be wider to avoid breaking words.
@classmethod
def _get_column_string_lengths(cls, dataset):
"""
Returns a list of string lengths of each column, and a list of
maximum word lengths.
"""
if dataset.headers:
column_lengths = [[len(h)] for h in dataset.headers]
word_lens = [_max_word_len(h) for h in dataset.headers]
else:
column_lengths = [[] for _ in range(dataset.width)]
word_lens = [0 for _ in range(dataset.width)]
for row in dataset.dict:
values = iter(row.values() if hasattr(row, 'values') else row)
for i, val in enumerate(values):
text = to_str(val)
column_lengths[i].append(len(text))
word_lens[i] = max(word_lens[i], _max_word_len(text))
return column_lengths, word_lens
@classmethod
def _row_to_lines(cls, values, widths, wrapper, sep='|', justify=JUSTIFY_LEFT):
"""
Returns a table row of wrapped values as a list of lines
"""
if justify not in JUSTIFY_VALUES:
raise ValueError('Value of "justify" must be one of "{}"'.format(
'", "'.join(JUSTIFY_VALUES)
))
if justify == JUSTIFY_LEFT:
just = lambda text, width: text.ljust(width)
elif justify == JUSTIFY_CENTER:
just = lambda text, width: text.center(width)
else:
just = lambda text, width: text.rjust(width)
lpad = sep + ' ' if sep else ''
rpad = ' ' + sep if sep else ''
pad = ' ' + sep + ' '
cells = []
for value, width in zip(values, widths):
wrapper.width = width
text = to_str(value)
cell = wrapper.wrap(text)
cells.append(cell)
lines = zip_longest(*cells, fillvalue='')
lines = (
(just(cell_line, widths[i]) for i, cell_line in enumerate(line))
for line in lines
)
lines = [''.join((lpad, pad.join(line), rpad)) for line in lines]
return lines
@classmethod
def _get_column_widths(cls, dataset, max_table_width=MAX_TABLE_WIDTH, pad_len=3):
"""
Returns a list of column widths proportional to the median length
of the text in their cells.
"""
str_lens, word_lens = cls._get_column_string_lengths(dataset)
median_lens = [int(median(lens)) for lens in str_lens]
total = sum(median_lens)
if total > max_table_width - (pad_len * len(median_lens)):
column_widths = (max_table_width * l // total for l in median_lens)
else:
column_widths = (l for l in median_lens)
# Allow for separator and padding:
column_widths = (w - pad_len if w > pad_len else w for w in column_widths)
# Rather widen table than break words:
column_widths = [max(w, l) for w, l in zip(column_widths, word_lens)]
return column_widths
@classmethod
def export_set_as_simple_table(cls, dataset, column_widths=None):
"""
Returns reStructuredText grid table representation of dataset.
"""
lines = []
wrapper = TextWrapper()
if column_widths is None:
column_widths = cls._get_column_widths(dataset, pad_len=2)
border = ' '.join(['=' * w for w in column_widths])
lines.append(border)
if dataset.headers:
lines.extend(cls._row_to_lines(
dataset.headers,
column_widths,
wrapper,
sep='',
justify=JUSTIFY_CENTER,
))
lines.append(border)
for row in dataset.dict:
values = iter(row.values() if hasattr(row, 'values') else row)
lines.extend(cls._row_to_lines(values, column_widths, wrapper, ''))
lines.append(border)
return '\n'.join(lines)
@classmethod
def export_set_as_grid_table(cls, dataset, column_widths=None):
"""
Returns reStructuredText grid table representation of dataset.
>>> from tablib import Dataset
>>> from tablib.formats import registry
>>> bits = ((0, 0), (1, 0), (0, 1), (1, 1))
>>> data = Dataset()
>>> data.headers = ['A', 'B', 'A and B']
>>> for a, b in bits:
... data.append([bool(a), bool(b), bool(a * b)])
>>> rst = registry.get_format('rst')
>>> print(rst.export_set(data, force_grid=True))
+-------+-------+-------+
| A | B | A and |
| | | B |
+=======+=======+=======+
| False | False | False |
+-------+-------+-------+
| True | False | False |
+-------+-------+-------+
| False | True | False |
+-------+-------+-------+
| True | True | True |
+-------+-------+-------+
"""
lines = []
wrapper = TextWrapper()
if column_widths is None:
column_widths = cls._get_column_widths(dataset)
header_sep = '+=' + '=+='.join(['=' * w for w in column_widths]) + '=+'
row_sep = '+-' + '-+-'.join(['-' * w for w in column_widths]) + '-+'
lines.append(row_sep)
if dataset.headers:
lines.extend(cls._row_to_lines(
dataset.headers,
column_widths,
wrapper,
justify=JUSTIFY_CENTER,
))
lines.append(header_sep)
for row in dataset.dict:
values = iter(row.values() if hasattr(row, 'values') else row)
lines.extend(cls._row_to_lines(values, column_widths, wrapper))
lines.append(row_sep)
return '\n'.join(lines)
@classmethod
def _use_simple_table(cls, head0, col0, width0):
"""
Use a simple table if the text in the first column is never wrapped
>>> from tablib.formats import registry
>>> rst = registry.get_format('rst')
>>> rst._use_simple_table('menu', ['egg', 'bacon'], 10)
True
>>> rst._use_simple_table(None, ['lobster thermidor', 'spam'], 10)
False
"""
if head0 is not None:
head0 = to_str(head0)
if len(head0) > width0:
return False
for cell in col0:
cell = to_str(cell)
if len(cell) > width0:
return False
return True
@classmethod
def export_set(cls, dataset, **kwargs):
"""
Returns reStructuredText table representation of dataset.
Returns a simple table if the text in the first column is never
wrapped, otherwise returns a grid table.
>>> from tablib import Dataset
>>> bits = ((0, 0), (1, 0), (0, 1), (1, 1))
>>> data = Dataset()
>>> data.headers = ['A', 'B', 'A and B']
>>> for a, b in bits:
... data.append([bool(a), bool(b), bool(a * b)])
>>> table = data.rst
>>> table.split('\\n') == [
... '===== ===== =====',
... ' A B A and',
... ' B ',
... '===== ===== =====',
... 'False False False',
... 'True False False',
... 'False True False',
... 'True True True ',
... '===== ===== =====',
... ]
True
"""
if not dataset.dict:
return ''
force_grid = kwargs.get('force_grid', False)
max_table_width = kwargs.get('max_table_width', cls.MAX_TABLE_WIDTH)
column_widths = cls._get_column_widths(dataset, max_table_width)
use_simple_table = cls._use_simple_table(
dataset.headers[0] if dataset.headers else None,
dataset.get_col(0),
column_widths[0],
)
if use_simple_table and not force_grid:
return cls.export_set_as_simple_table(dataset, column_widths)
else:
return cls.export_set_as_grid_table(dataset, column_widths)
@classmethod
def export_book(cls, databook):
"""
reStructuredText representation of a Databook.
Tables are separated by a blank line. All tables use the grid
format.
"""
return '\n\n'.join(cls.export_set(dataset, force_grid=True)
for dataset in databook._datasets)
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