def main():
arg_parser = argparse.ArgumentParser(
description=
'Create a pdf document from a exported csv of Pivotal Tracker',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
arg_parser.add_argument('csv', help='the file path to the csv file')
arg_parser.add_argument('-m',
'--margin',
type=int,
default=5,
help='margin of the page in mm')
arg_parser.add_argument('-o',
'--output',
help='file path to the generated pdf')
arg_parser.add_argument('-n',
'--show-number',
action='store_true',
help='shows the story number on the bottom left')
arg_parser.add_argument('-t',
'--show-tasks',
action='store_true',
help='shows the tasks for each story')
arg_parser.add_argument(
'-c',
'--collate',
action='store_true',
help='collate stories for easier sorting after cutting all pages')
arg_parser.add_argument(
'-s',
'--strict',
action='store_true',
help='fails if the csv file does not contain all required columns')
args = arg_parser.parse_args()
output_file = args.output if args.output is not None \
else os.path.splitext(args.csv)[0] + '.pdf'
page_margin = args.margin
story_width = (297 - (page_margin * 2)) / 2
story_height = (210 - (page_margin * 2)) / 2
stories = []
with open(args.csv, 'r') as csvfile:
reader = csv.reader(csvfile, delimiter=',')
data = list(reader)
if args.strict:
validate_columns(data[0])
stories = map(partial(make_pivotal_story, data[0]),
enumerate(data[1:], 1))
pdf = Pdf()
pdf.set_auto_page_break(False)
positions = [(page_margin, page_margin),
(page_margin + story_width, page_margin),
(page_margin, page_margin + story_height),
(page_margin + story_width, page_margin + story_height)]
stories = list(iterstories(stories, include_tasks=args.show_tasks))
chunk_function = stacked_chunks if args.collate else chunks
for story_chunk in chunk_function(stories, 4):
pdf.add_page('Landscape')
for story, position in zip(story_chunk, positions):
story.draw(
pdf,
position[0],
position[1],
story_width,
story_height,
args.show_number,
)
pdf.output(output_file)
open_file(output_file)
return output_file