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gristlabs_grist-core/sandbox/grist/imports/import_csv.py

259 lines
8.5 KiB

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