def summary():
'''
summerize all the promising stock information
'''
summaries = []
for s in st_list[:20]:
summaries.append(get_information(s))
text = tabulate(summaries, headers = 'keys', tablefmt='fancy_grid')
print(text)
table_html = tabulate(summaries, headers = 'keys', tablefmt='html')
return table_html
def summary():
'''
summerize all the promising stock information
'''
summaries = []
for s in st_list[:20]:
summaries.append(get_information(s))
text = tabulate(summaries, headers='keys', tablefmt='fancy_grid')
print(text)
table_html = tabulate(summaries, headers='keys', tablefmt='html')
return table_html
def dump_tabular(self, *args, **kwargs):
wh = kwargs.pop("write_header", None)
if len(self._tabular) > 0:
for line in tabulate(self._tabular).split('\n'):
self.log(line, *args, **kwargs)
tabular_dict = dict(self._tabular)
for tabular_fd in list(self._tabular_fds.values()):
writer = csv.DictWriter(tabular_fd,
fieldnames=list(tabular_dict.keys()))
if wh or (wh is None
and tabular_fd not in self._tabular_header_written):
writer.writeheader()
self._tabular_header_written.add(tabular_fd)
writer.writerow(tabular_dict)
tabular_fd.flush()
del self._tabular[:]
def tabulate(data, headr=(), formatters=(), inds='nice'):
"""Pre-processor for tabulate().
data: list-of-lists, whose 'rows' will be printed as columns.
This coincides with the output of Dict.values().
headr: list or tuple.
If 'data' is a dict, then the keys will be the headr.
formatter: define formats to apply before relaying to pandas.
Default: attr.__name__ (when applicable).
Example:
>>> print(tabulate(cfgs.distinct_attrs()))
"""
# Extract headr/mattr
if hasattr(data, 'keys'):
headr = list(data)
data = data.values()
# Default formats
if not formatters:
formatters = ({
'test': lambda x: hasattr(x, '__name__'),
'format': lambda x: x.__name__
}, )
# Apply formatting (if not applicable, data is just forwarded)
for f in formatters:
data = [[f['format'](j) for j in row] if f['test'](row[0]) else row
for row in data]
# Transpose
data = list(map(list, zip(*data)))
# Generate nice indices
if inds == 'nice':
inds = ['[{}]'.format(d) for d in range(len(data))]
else:
pass # Should be True or False
return tabulate_orig.tabulate(data, headr, showindex=inds)