dbt-selly/dbt-env/lib/python3.8/site-packages/agate/table/from_csv.py

89 lines
2.6 KiB
Python

#!/usr/bin/env python
import io
import six
@classmethod
def from_csv(cls, path, column_names=None, column_types=None, row_names=None, skip_lines=0, header=True, sniff_limit=0, encoding='utf-8', **kwargs):
"""
Create a new table from a CSV.
This method uses agate's builtin CSV reader, which supplies encoding
support for both Python 2 and Python 3.
:code:`kwargs` will be passed through to the CSV reader.
:param path:
Filepath or file-like object from which to read CSV data. If a file-like
object is specified, it must be seekable. If using Python 2, the file
should be opened in binary mode (`rb`).
:param column_names:
See :meth:`.Table.__init__`.
:param column_types:
See :meth:`.Table.__init__`.
:param row_names:
See :meth:`.Table.__init__`.
:param skip_lines:
The number of lines to skip from the top of the file. Note that skip
lines will not work with
:param header:
If :code:`True`, the first row of the CSV is assumed to contain column
names. If :code:`header` and :code:`column_names` are both specified
then a row will be skipped, but :code:`column_names` will be used.
:param sniff_limit:
Limit CSV dialect sniffing to the specified number of bytes. Set to
None to sniff the entire file. Defaults to 0 (no sniffing).
:param encoding:
Character encoding of the CSV file. Note: if passing in a file
handle it is assumed you have already opened it with the correct
encoding specified.
"""
from agate import csv
from agate.table import Table
close = False
if hasattr(path, 'read'):
f = path
else:
if six.PY2:
f = open(path, 'Urb')
else:
f = io.open(path, encoding=encoding)
close = True
if isinstance(skip_lines, int):
while skip_lines > 0:
f.readline()
skip_lines -= 1
else:
raise ValueError('skip_lines argument must be an int')
contents = six.StringIO(f.read())
if sniff_limit is None:
kwargs['dialect'] = csv.Sniffer().sniff(contents.getvalue())
elif sniff_limit > 0:
kwargs['dialect'] = csv.Sniffer().sniff(contents.getvalue()[:sniff_limit])
if six.PY2:
kwargs['encoding'] = encoding
reader = csv.reader(contents, header=header, **kwargs)
if header:
if column_names is None:
column_names = next(reader)
else:
next(reader)
rows = tuple(reader)
if close:
f.close()
return Table(rows, column_names, column_types, row_names=row_names)