def refresh(self):
import os
rows, columns = os.popen('stty size', 'r').read().split()
tabulars = self.tabulars[-(int(rows) - 3):]
sys.stdout.write("\x1b[2J\x1b[H")
sys.stdout.write(tabulate(tabulars, self.headers))
sys.stdout.write("\n")
def dump_tabular(*args, **kwargs):
if not _disabled: # and not _tabular_disabled:
wh = kwargs.pop("write_header", None)
if len(_tabular) > 0:
if _log_tabular_only:
table_printer.print_tabular(_tabular)
else:
for line in tabulate(_tabular).split("\n"):
log(line, *args, **kwargs)
if not _tabular_disabled:
tabular_dict = dict(_tabular)
# Also write to the csv files
# This assumes that the keys in each iteration won't change!
for tabular_file_name, tabular_fd in list(
_tabular_fds.items()):
keys = tabular_dict.keys()
if tabular_file_name in _tabular_headers:
# check against existing keys: if new keys re-write Header and pad with NaNs
existing_keys = _tabular_headers[tabular_file_name]
if not set(existing_keys).issuperset(set(keys)):
joint_keys = set(keys).union(set(existing_keys))
tabular_fd.flush()
read_fd = open(tabular_file_name, "r")
reader = csv.DictReader(read_fd)
rows = list(reader)
read_fd.close()
tabular_fd.close()
tabular_fd = _tabular_fds[
tabular_file_name] = open(
tabular_file_name, "w")
new_writer = csv.DictWriter(
tabular_fd, fieldnames=list(joint_keys))
new_writer.writeheader()
for row in rows:
for key in joint_keys:
if key not in row:
row[key] = np.nan
new_writer.writerows(rows)
_tabular_headers[tabular_file_name] = list(
joint_keys)
else:
_tabular_headers[tabular_file_name] = keys
writer = csv.DictWriter(
tabular_fd,
fieldnames=_tabular_headers[tabular_file_name]
) # list(
if wh or (wh is None and tabular_file_name
not in _tabular_header_written):
writer.writeheader()
_tabular_header_written.add(tabular_file_name)
_tabular_headers[tabular_file_name] = keys
# add NaNs in all empty fields from the header
for key in _tabular_headers[tabular_file_name]:
if key not in tabular_dict:
tabular_dict[key] = np.nan
writer.writerow(tabular_dict)
tabular_fd.flush()
del _tabular[:]
