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259 lines
8.5 KiB
259 lines
8.5 KiB
"""
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Plugin for importing CSV files
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"""
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import codecs
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import csv
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import logging
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import chardet
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import six
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from six.moves import zip
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import parse_data
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from imports import import_utils
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log = logging.getLogger(__name__)
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log.setLevel(logging.INFO)
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SCHEMA = [
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{
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'name': 'lineterminator',
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'label': 'Line terminator',
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'type': 'string',
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'visible': True,
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},
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{
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'name': 'include_col_names_as_headers',
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'label': 'First row contains headers',
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'type': 'boolean',
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'visible': True,
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},
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{
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'name': 'delimiter',
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'label': 'Field separator',
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'type': 'string',
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'visible': True,
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},
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{
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'name': 'skipinitialspace',
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'label': 'Skip leading whitespace',
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'type': 'boolean',
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'visible': True,
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},
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{
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'name': 'quotechar',
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'label': 'Quote character',
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'type': 'string',
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'visible': True,
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},
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{
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'name': 'doublequote',
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'label': 'Quotes in fields are doubled',
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'type': 'boolean',
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'visible': True,
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},
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{
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'name': 'quoting',
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'label': 'Convert quoted fields',
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'type': 'number',
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'visible': False, # Not supported by messytables
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},
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{
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'name': 'escapechar',
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'label': 'Escape character',
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'type': 'string',
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'visible': False, # Not supported by messytables
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},
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{
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'name': 'start_with_row',
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'label': 'Start with row',
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'type': 'number',
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'visible': False, # Not yet implemented
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},
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{
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'name': 'NUM_ROWS',
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'label': 'Number of rows',
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'type': 'number',
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'visible': False,
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},
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{
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'name': 'encoding',
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'label': 'Character encoding. See https://tinyurl.com/py3codecs',
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'type': 'string',
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'visible': True,
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}
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]
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def parse_file_source(file_source, options):
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parsing_options, export_list = parse_file(import_utils.get_path(file_source["path"]), options)
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return {"parseOptions": parsing_options, "tables": export_list}
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def parse_file(file_path, parse_options=None):
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"""
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Reads a file path and parse options that are passed in using ActiveDoc.importFile()
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and returns a tuple with parsing options (users' or guessed) and an object formatted so that
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it can be used by grist for a bulk add records action.
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"""
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parse_options = parse_options or {}
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given_encoding = parse_options.get('encoding')
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encoding = given_encoding or detect_encoding(file_path)
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log.info("Using encoding %s (%s)", encoding, "given" if given_encoding else "detected")
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try:
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return _parse_with_encoding(file_path, parse_options, encoding)
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except Exception as e:
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encoding = 'utf-8'
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# For valid encodings, we can do our best and report count of errors. But an invalid encoding
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# or one with a BOM will produce an exception. For those, fall back to utf-8.
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parsing_options, export_list = _parse_with_encoding(file_path, parse_options, encoding)
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parsing_options["WARNING"] = "{}: {}. Falling back to {}.\n{}".format(
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type(e).__name__, e, encoding, parsing_options.get("WARNING", ""))
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return parsing_options, export_list
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def _parse_with_encoding(file_path, parse_options, encoding):
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codec_errors = CodecErrorsReplace()
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codecs.register_error('custom', codec_errors)
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with codecs.open(file_path, mode="r", encoding=encoding, errors="custom") as f:
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parsing_options, export_list = _parse_open_file(f, parse_options=parse_options)
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parsing_options["encoding"] = encoding
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if codec_errors.error_count:
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parsing_options["WARNING"] = (
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"Using encoding %s, encountered %s errors. Use Import Options to change" %
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(encoding, codec_errors.error_count))
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return parsing_options, export_list
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def _guess_dialect(file_obj):
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try:
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# Restrict allowed delimiters to prevent guessing other char than this list.
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dialect = csv.Sniffer().sniff(file_obj.read(100000), delimiters=['\t', ',', ';', '|'])
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log.info("Guessed dialect %s", dict(dialect.__dict__))
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# Mimic messytables default for now.
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dialect.lineterminator = "\n"
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dialect.doublequote = True
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return dialect
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except csv.Error:
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log.info("Cannot guess dialect using Excel as fallback.")
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return csv.excel
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finally:
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file_obj.seek(0)
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def _parse_open_file(file_obj, parse_options=None):
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csv_keys = ['delimiter', 'quotechar', 'lineterminator', 'doublequote', 'skipinitialspace']
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options = {}
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dialect = _guess_dialect(file_obj)
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csv_options = {}
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for key in csv_keys:
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value = parse_options.get(key, getattr(dialect, key, None))
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if value is not None:
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csv_options[key] = value
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reader = csv.reader(file_obj, **csv_options)
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rows = list(reader)
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sample_len = 100
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sample_rows = rows[:sample_len]
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data_offset, headers = import_utils.headers_guess(sample_rows)
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# Make sure all header values are strings.
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for i, header in enumerate(headers):
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if not isinstance(header, six.string_types):
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headers[i] = six.text_type(header)
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log.info("Guessed data_offset as %s", data_offset)
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log.info("Guessed headers as: %s", headers)
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have_guessed_headers = any(headers)
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include_col_names_as_headers = parse_options.get('include_col_names_as_headers',
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have_guessed_headers)
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if include_col_names_as_headers and not have_guessed_headers:
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# use first line as headers
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data_offset, first_row = import_utils.find_first_non_empty_row(sample_rows)
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headers = import_utils.expand_headers(first_row, data_offset, sample_rows)
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elif not include_col_names_as_headers and have_guessed_headers:
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# move guessed headers to data
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data_offset -= 1
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headers = [''] * len(headers)
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rows = rows[data_offset:]
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num_rows = parse_options.get('NUM_ROWS', 0)
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table_data_with_types = parse_data.get_table_data(rows, len(headers), num_rows)
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# Identify and remove empty columns, and populate separate metadata and data lists.
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column_metadata = []
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table_data = []
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for col_data, header in zip(table_data_with_types, headers):
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if not header and all(val == "" for val in col_data["data"]):
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continue # empty column
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data = col_data.pop("data")
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col_data["id"] = header
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column_metadata.append(col_data)
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table_data.append(data)
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if not table_data:
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log.info("No data found. Aborting CSV import.")
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# Don't add tables with no columns.
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return {}, []
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guessed = reader.dialect
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quoting = parse_options.get('quoting')
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options = {"delimiter": parse_options.get('delimiter', guessed.delimiter),
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"doublequote": parse_options.get('doublequote', guessed.doublequote),
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"lineterminator": parse_options.get('lineterminator', guessed.lineterminator),
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"quotechar": parse_options.get('quotechar', guessed.quotechar),
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"skipinitialspace": parse_options.get('skipinitialspace', guessed.skipinitialspace),
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"include_col_names_as_headers": include_col_names_as_headers,
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"start_with_row": 1,
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"NUM_ROWS": num_rows,
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"SCHEMA": SCHEMA
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}
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log.info("Output table with %d columns", len(column_metadata))
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for c in column_metadata:
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log.debug("Output column %s", c)
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export_list = [{
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"table_name": None,
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"column_metadata": column_metadata,
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"table_data": table_data
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}]
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return options, export_list
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class CodecErrorsReplace(object):
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def __init__(self):
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self.error_count = 0
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self.first_error = None
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def __call__(self, error):
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self.error_count += 1
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if not self.first_error:
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self.first_error = error
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return codecs.replace_errors(error)
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def detect_encoding(file_path):
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# Use line-by-line detection as suggested in
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# https://chardet.readthedocs.io/en/latest/usage.html#advanced-usage.
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# Using a fixed-sized sample is worse as the sample may end mid-character.
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detector = chardet.UniversalDetector()
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with codecs.open(file_path, "rb") as f:
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for line in f.readlines():
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detector.feed(line)
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if detector.done:
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break
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detector.close()
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encoding = detector.result["encoding"]
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# Default to utf-8, and always prefer it over ASCII as the most common superset.
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if not encoding or encoding == 'ascii':
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encoding = 'utf-8'
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return encoding
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