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