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from django.template import loader
from regulations.generator.layers.base import SearchReplaceLayer
class FormattingLayer(SearchReplaceLayer):
shorthand = 'formatting'
data_source = 'formatting'
DATA_TYPES = ('table', 'fence', 'subscript', 'dash', 'footnote',
'superscript')
def __init__(self, layer):
self.layer = layer
self.tpls = {
key: loader.get_template('regulations/layers/{}.html'.format(key))
for key in ('table', 'note', 'code', 'subscript', 'dash',
'footnote', 'superscript')}
def render_table(self, table, data_type=None):
max_width = 0
for header_row in table['header']:
width = sum(cell['colspan'] for cell in header_row)
max_width = max(max_width, width)
# Just in case a row is longer than the header
row_max = max(len(row) for row in table['rows'])
max_width = max(max_width, row_max)
# Now pad rows if needed
for row in table['rows']:
row.extend([''] * (max_width - len(row)))
# Remove new lines so that they don't get escaped on display
return self.tpls['table'].render(table).replace('\n', '')
def render_fence(self, fence, data_type=None):
"""Fenced paragraphs are formatted separately, offset from the rest of
the text. They have an associated "type" which further specifies their
format"""
_type = fence.get('type')
lines = fence.get('lines', [])
strip_nl = True
if _type == 'note':
lines = [l.replace('Note:', '').replace('Notes:', '')
for l in lines]
lines = [l for l in lines if l.strip()]
tpl = self.tpls['note']
else: # Generic "code"/ preformatted
strip_nl = False
tpl = self.tpls['code']
rendered = tpl.render({'lines': lines, 'type': _type})
if strip_nl:
rendered = rendered.replace('\n', '')
return rendered
def render_replacement(self, data, data_type):
"""Several of the formatted data types are simple string replacements.
Implement them all here"""
return self.tpls[data_type].render(data).replace('\n', '')
def replacements_for(self, original, data):
for data_type in self.DATA_TYPES:
processor = getattr(self, 'render_' + data_type,
self.render_replacement)
key = data_type + '_data'
if key in data:
yield processor(data[key], data_type)