# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function, unicode_literals
try:
import numpy as np
except ImportError as ex:
pass
from six.moves import zip, map
import six
from utool import util_type
from utool import util_inject
print, rrr, profile = util_inject.inject2(__name__, '[csv]')
[docs]def numpy_to_csv(arr, col_lbls=None, header='', col_type=None):
col_list = arr.T.tolist()
return make_csv_table(col_list, col_lbls, header, col_type)
[docs]def read_csv(fpath):
""" reads csv in unicode """
import csv
import utool as ut
#csvfile = open(fpath, 'rb')
with open(fpath, 'rb') as csvfile:
row_iter = csv.reader(csvfile, delimiter=str(','), quotechar=str('|'))
row_list = [ut.lmap(ut.ensure_unicode, row) for row in row_iter]
return row_list
[docs]def make_csv_table(column_list=[], column_lbls=None, header='',
column_type=None, row_lbls=None, transpose=False,
precision=2, use_lbl_width=True, comma_repl='<comma>', raw=False):
"""
Creates a csv table with aligned columns
make_csv_table
Args:
column_list (list):
column_lbls (None):
header (str):
column_type (None):
row_lbls (None):
transpose (bool):
Returns:
str: csv_text
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_csv import * # NOQA
>>> column_list = [[1, 2, 3], ['A', 'B', 'C']]
>>> column_lbls = ['num', 'alpha']
>>> header = '# Test CSV'
>>> column_type = (int, str)
>>> row_lbls = None
>>> transpose = False
>>> csv_text = make_csv_table(column_list, column_lbls, header, column_type, row_lbls, transpose)
>>> result = csv_text
>>> print(result)
# Test CSV
# num_rows=3
# num, alpha
1, A
2, B
3, C
"""
import utool as ut
assert comma_repl.find(',') == -1, 'comma_repl cannot contain a comma!'
if transpose:
column_lbls, row_lbls = row_lbls, column_lbls
column_list = list(map(list, zip(*column_list)))
#import utool as ut
#ut.embed()
#column_lbls = row_lbls[0]
#row_list =
if row_lbls is not None:
if isinstance(column_list, np.ndarray):
column_list = column_list.tolist()
if isinstance(row_lbls, np.ndarray):
row_lbls = row_lbls.tolist()
column_list = [row_lbls] + column_list
column_lbls = ['ROWLBL'] + list(map(six.text_type, column_lbls))
if column_type is not None:
column_type = [six.text_type] + column_type
if len(column_list) == 0:
print('[csv] No columns')
return header
column_len = [len(col) for col in column_list]
num_data = column_len[0]
if num_data == 0:
#print('[csv.make_csv_table()] No data. (header=%r)' % (header,))
return header
if any([num_data != clen for clen in column_len]):
print('[csv] column_lbls = %r ' % (column_lbls,))
print('[csv] column_len = %r ' % (column_len,))
print('[csv] inconsistent column lengths')
return header
if column_type is None:
column_type = list(map(type, ut.get_list_column(column_list, 0)))
#column_type = [type(col[0]) for col in column_list]
csv_rows = []
if not raw:
csv_rows.append(header)
csv_rows.append('# num_rows=%r' % num_data)
column_maxlen = []
column_str_list = []
if column_lbls is None:
column_lbls = [''] * len(column_list)
def _toint(c):
if c is None:
return 'None'
try:
if np.isnan(c):
return 'nan'
except TypeError as ex:
print('------')
print('[csv] TypeError %r ' % ex)
print('[csv] _toint(c) failed')
print('[csv] c = %r ' % c)
print('[csv] type(c) = %r ' % type(c))
print('------')
raise
return ('%d') % int(c)
try:
# Loop over every column
for col, lbl, coltype in zip(column_list, column_lbls, column_type):
# Loop over every row in the column (using list comprehension)
if coltype is list or util_type.is_list(coltype):
#print('list')
#col_str = [six.text_type(c).replace(',', comma_repl).replace('.', '<dot>') for c in (col)]
col_str = [six.text_type(c).replace(',', ' ').replace('.', '<dot>') for c in col]
elif (coltype is float or
util_type.is_float(coltype) or
coltype == np.float32 or
util_type.is_valid_floattype(coltype)):
precision_fmtstr = '%.' + six.text_type(precision) + 'f'
col_str = ['None' if r is None else precision_fmtstr % float(r) for r in col]
elif coltype is int or util_type.is_int(coltype) or coltype == np.int64:
col_str = [_toint(c) for c in (col)]
elif coltype is six.text_type or coltype is six.text_type or util_type.is_str(coltype):
if coltype is six.text_type:
col_str = [six.text_type(c).replace(',', comma_repl) for c in col]
else:
col_str = [six.text_type(c).replace(',', comma_repl) for c in col]
else:
print('[csv] is_unknown coltype=%r' % (coltype,))
col_str = [six.text_type(c) for c in (col)]
col_lens = [len(s) for s in (col_str)]
max_len = max(col_lens)
if use_lbl_width:
# The column label counts towards the column width
max_len = max(len(lbl), max_len)
column_maxlen.append(max_len)
column_str_list.append(col_str)
except Exception as ex:
#ut.embed()
ut.printex(ex, keys=['col', 'lbl', 'coltype'])
raise
def _fmtfn(maxlen):
return ''.join(['%', six.text_type(maxlen + 2), 's'])
fmtstr = ','.join([_fmtfn(maxlen) for maxlen in column_maxlen])
try:
if not raw:
csv_rows.append('# ' + fmtstr % tuple(column_lbls))
#csv_rows.append('# ' + fmtstr % column_lbls)
except Exception as ex:
#print(len(column_list))
#ut.embed()
ut.printex(ex, keys=['fmtstr', 'column_lbls'])
raise
for row in zip(*column_str_list):
csv_rows.append(' ' + fmtstr % row)
csv_text = '\n'.join(csv_rows)
return csv_text
if __name__ == '__main__':
"""
CommandLine:
python -c "import utool, utool.util_csv; utool.doctest_funcs(utool.util_csv, allexamples=True)"
python -c "import utool, utool.util_csv; utool.doctest_funcs(utool.util_csv)"
python -m utool.util_csv
python -m utool.util_csv --allexamples
"""
import multiprocessing
multiprocessing.freeze_support() # for win32
import utool as ut # NOQA
ut.doctest_funcs()