Files
odoo_source/addons/base_import/models.py
T
Xavier Morel a4ee8e5723 [IMP] base_import: use mimetype guessing
Rather than trust the user-controlled mimetype or extension of imported
files which may be incorrect (because the user is lying, because the
system is misconfigured, because software is not installed, because
software is registering non-standard mimetypes, etc...), start by trying
to guess the mimetype *then* fallback on trying the type/ext.

Of note: CSV is becoming less and less great as it's nigh impossible to
guess for it.
2016-02-17 15:45:11 +01:00

473 lines
19 KiB
Python

import csv
import datetime
import io
import itertools
import logging
import operator
import os
from openerp.tools.mimetypes import guess_mimetype
try:
from cStringIO import StringIO
except ImportError:
from StringIO import StringIO
import psycopg2
from openerp.osv import orm, fields
from openerp.tools.translate import _
from openerp.tools import DEFAULT_SERVER_DATE_FORMAT, \
DEFAULT_SERVER_DATETIME_FORMAT
FIELDS_RECURSION_LIMIT = 2
ERROR_PREVIEW_BYTES = 200
_logger = logging.getLogger(__name__)
try:
import xlrd
try:
from xlrd import xlsx
except ImportError:
xlsx = None
except ImportError:
xlrd = xlsx = None
try:
import odf_ods_reader
except ImportError:
odf_ods_reader = None
FILE_TYPE_DICT = {
'text/csv': ('csv', True, None),
'application/vnd.ms-excel': ('xls', xlrd, 'xlrd'),
'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': ('xlsx', xlsx, 'xlrd >= 0.8'),
'application/vnd.oasis.opendocument.spreadsheet': ('ods', odf_ods_reader, 'odfpy')
}
EXTENSIONS = {
'.' + ext: handler
for mime, (ext, handler, req) in FILE_TYPE_DICT.iteritems()
}
class ir_import(orm.TransientModel):
_name = 'base_import.import'
# allow imports to survive for 12h in case user is slow
_transient_max_hours = 12.0
_columns = {
'res_model': fields.char('Model'),
'file': fields.binary(
'File', help="File to check and/or import, raw binary (not base64)"),
'file_name': fields.char('File Name'),
'file_type': fields.char(string='File Type'),
}
def get_fields(self, cr, uid, model, context=None,
depth=FIELDS_RECURSION_LIMIT):
""" Recursively get fields for the provided model (through
fields_get) and filter them according to importability
The output format is a list of ``Field``, with ``Field``
defined as:
.. class:: Field
.. attribute:: id (str)
A non-unique identifier for the field, used to compute
the span of the ``required`` attribute: if multiple
``required`` fields have the same id, only one of them
is necessary.
.. attribute:: name (str)
The field's logical (Odoo) name within the scope of
its parent.
.. attribute:: string (str)
The field's human-readable name (``@string``)
.. attribute:: required (bool)
Whether the field is marked as required in the
model. Clients must provide non-empty import values
for all required fields or the import will error out.
.. attribute:: fields (list(Field))
The current field's subfields. The database and
external identifiers for m2o and m2m fields; a
filtered and transformed fields_get for o2m fields (to
a variable depth defined by ``depth``).
Fields with no sub-fields will have an empty list of
sub-fields.
:param str model: name of the model to get fields form
:param int landing: depth of recursion into o2m fields
"""
model_obj = self.pool[model]
fields = [{
'id': 'id',
'name': 'id',
'string': _("External ID"),
'required': False,
'fields': [],
}]
fields_got = model_obj.fields_get(cr, uid, context=context)
blacklist = orm.MAGIC_COLUMNS + [model_obj.CONCURRENCY_CHECK_FIELD]
for name, field in fields_got.iteritems():
if name in blacklist:
continue
# an empty string means the field is deprecated, @deprecated must
# be absent or False to mean not-deprecated
if field.get('deprecated', False) is not False:
continue
if field.get('readonly'):
states = field.get('states')
if not states:
continue
# states = {state: [(attr, value), (attr2, value2)], state2:...}
if not any(attr == 'readonly' and value is False
for attr, value in itertools.chain.from_iterable(
states.itervalues())):
continue
f = {
'id': name,
'name': name,
'string': field['string'],
# Y U NO ALWAYS HAS REQUIRED
'required': bool(field.get('required')),
'fields': [],
}
if field['type'] in ('many2many', 'many2one'):
f['fields'] = [
dict(f, name='id', string=_("External ID")),
dict(f, name='.id', string=_("Database ID")),
]
elif field['type'] == 'one2many' and depth:
f['fields'] = self.get_fields(
cr, uid, field['relation'], context=context, depth=depth-1)
if self.user_has_groups(cr, uid, 'base.group_no_one'):
f['fields'].append({'id' : '.id', 'name': '.id', 'string': _("Database ID"), 'required': False, 'fields': []})
fields.append(f)
# TODO: cache on model?
return fields
def _read_file(self, file_type, record, options):
# guess mimetype from file content
mimetype = guess_mimetype(record.file)
(file_extension, handler, req) = FILE_TYPE_DICT.get(mimetype, (None, None, None))
if handler:
try:
return getattr(self, '_read_' + file_extension)(record, options)
except Exception:
_logger.warn("Failed to read file '%s' (transient id %d) using guessed mimetype %s",
record.file_name or '<unknown>', record.id, mimetype)
# try reading with user-provided mimetype
(file_extension, handler, req) = FILE_TYPE_DICT.get(file_type, (None, None, None))
if handler:
try:
return getattr(self, '_read_' + file_extension)(record, options)
except Exception:
_logger.warn("Failed to read file '%s' (transient id %d) using user-provided mimetype %s",
record.file_name or '<unknown>', record.id, file_type)
# fallback on file extensions as mime types can be unreliable (e.g.
# software setting incorrect mime types, or non-installed software
# leading to browser not sending mime types)
if record.file_name:
p, ext = os.path.splitext(record.file_name)
if ext in EXTENSIONS:
try:
return getattr(self, '_read_' + ext[1:])(record, options)
except Exception:
_logger.warn("Failed to read file '%s' (transient id %s) using file extension",
record.file_name, record.id)
if req:
raise ImportError(_("Unable to load \"{extension}\" file: requires Python module \"{modname}\"").format(extension=file_extension, modname=req))
raise ValueError(_("Unsupported file format \"{}\", import only supports CSV, ODS, XLS and XLSX").format(file_type))
def _read_xls(self, record, options):
book = xlrd.open_workbook(file_contents=record.file)
sheet = book.sheet_by_index(0)
# emulate Sheet.get_rows for pre-0.9.4
for row in itertools.imap(sheet.row, range(sheet.nrows)):
values = []
for cell in row:
if cell.ctype is xlrd.XL_CELL_NUMBER:
is_float = cell.value % 1 != 0.0
values.append(
unicode(cell.value)
if is_float
else unicode(int(cell.value))
)
elif cell.ctype is xlrd.XL_CELL_DATE:
is_datetime = cell.value % 1 != 0.0
# emulate xldate_as_datetime for pre-0.9.3
dt = datetime.datetime(*xlrd.xldate.xldate_as_tuple(
cell.value, book.datemode))
values.append(
dt.strftime(DEFAULT_SERVER_DATETIME_FORMAT)
if is_datetime
else dt.strftime(DEFAULT_SERVER_DATE_FORMAT)
)
elif cell.ctype is xlrd.XL_CELL_BOOLEAN:
values.append(u'True' if cell.value else u'False')
elif cell.ctype is xlrd.XL_CELL_ERROR:
raise ValueError(
_("Error cell found while reading XLS/XLSX file: %s") %
xlrd.error_text_from_code.get(
cell.value, "unknown error code %s" % cell.value)
)
else:
values.append(cell.value)
if any(x for x in values if x.strip()):
yield values
_read_xlsx = _read_xls
def _read_ods(self, record, options):
doc = odf_ods_reader.ODSReader(file=io.BytesIO(record.file))
return (
row
for row in doc.getFirstSheet()
if any(x for x in row if x.strip())
)
def _read_csv(self, record, options):
""" Returns a CSV-parsed iterator of all empty lines in the file
:throws csv.Error: if an error is detected during CSV parsing
:throws UnicodeDecodeError: if ``options.encoding`` is incorrect
"""
csv_iterator = csv.reader(
StringIO(record.file),
quotechar=str(options['quoting']),
delimiter=str(options['separator']))
# TODO: guess encoding with chardet? Or https://github.com/aadsm/jschardet
encoding = options.get('encoding', 'utf-8')
return (
[item.decode(encoding) for item in row]
for row in csv_iterator
if any(x for x in row if x.strip())
)
def _match_header(self, header, fields, options):
""" Attempts to match a given header to a field of the
imported model.
:param str header: header name from the CSV file
:param fields:
:param dict options:
:returns: an empty list if the header couldn't be matched, or
all the fields to traverse
:rtype: list(Field)
"""
string_match = None
for field in fields:
# FIXME: should match all translations & original
# TODO: use string distance (levenshtein? hamming?)
if header.lower() == field['name'].lower():
return [field]
if header.lower() == field['string'].lower():
# matching string are not reliable way because
# strings have no unique constraint
string_match = field
if string_match:
# this behavior is only applied if there is no matching field['name']
return [string_match]
if '/' not in header:
return []
# relational field path
traversal = []
subfields = fields
# Iteratively dive into fields tree
for section in header.split('/'):
# Strip section in case spaces are added around '/' for
# readability of paths
match = self._match_header(section.strip(), subfields, options)
# Any match failure, exit
if not match: return []
# prep subfields for next iteration within match[0]
field = match[0]
subfields = field['fields']
traversal.append(field)
return traversal
def _match_headers(self, rows, fields, options):
""" Attempts to match the imported model's fields to the
titles of the parsed CSV file, if the file is supposed to have
headers.
Will consume the first line of the ``rows`` iterator.
Returns a pair of (None, None) if headers were not requested
or the list of headers and a dict mapping cell indices
to key paths in the ``fields`` tree
:param Iterator rows:
:param dict fields:
:param dict options:
:rtype: (None, None) | (list(str), dict(int: list(str)))
"""
if not options.get('headers'):
return None, None
headers = next(rows)
return headers, {
index: [field['name'] for field in self._match_header(header, fields, options)] or None
for index, header in enumerate(headers)
}
def parse_preview(self, cr, uid, id, options, count=10, context=None):
""" Generates a preview of the uploaded files, and performs
fields-matching between the import's file data and the model's
columns.
If the headers are not requested (not options.headers),
``matches`` and ``headers`` are both ``False``.
:param id: identifier of the import
:param int count: number of preview lines to generate
:param options: format-specific options.
CSV: {encoding, quoting, separator, headers}
:type options: {str, str, str, bool}
:returns: {fields, matches, headers, preview} | {error, preview}
:rtype: {dict(str: dict(...)), dict(int, list(str)), list(str), list(list(str))} | {str, str}
"""
(record,) = self.browse(cr, uid, [id], context=context)
fields = self.get_fields(cr, uid, record.res_model, context=context)
try:
rows = self._read_file(record.file_type, record, options)
headers, matches = self._match_headers(rows, fields, options)
# Match should have consumed the first row (iif headers), get
# the ``count`` next rows for preview
preview = list(itertools.islice(rows, count))
assert preview, "CSV file seems to have no content"
return {
'fields': fields,
'matches': matches or False,
'headers': headers or False,
'preview': preview,
}
except Exception, e:
# Due to lazy generators, UnicodeDecodeError (for
# instance) may only be raised when serializing the
# preview to a list in the return.
_logger.debug("Error during parsing preview", exc_info=True)
preview = None
if record.file_type == 'text/csv':
preview = record.file[:ERROR_PREVIEW_BYTES].decode('iso-8859-1')
return {
'error': str(e),
# iso-8859-1 ensures decoding will always succeed,
# even if it yields non-printable characters. This is
# in case of UnicodeDecodeError (or csv.Error
# compounded with UnicodeDecodeError)
'preview': preview,
}
def _convert_import_data(self, record, fields, options, context=None):
""" Extracts the input browse_record and fields list (with
``False``-y placeholders for fields to *not* import) into a
format Model.import_data can use: a fields list without holes
and the precisely matching data matrix
:param browse_record record:
:param list(str|bool): fields
:returns: (data, fields)
:rtype: (list(list(str)), list(str))
:raises ValueError: in case the import data could not be converted
"""
# Get indices for non-empty fields
indices = [index for index, field in enumerate(fields) if field]
if not indices:
raise ValueError(_("You must configure at least one field to import"))
# If only one index, itemgetter will return an atom rather
# than a 1-tuple
if len(indices) == 1: mapper = lambda row: [row[indices[0]]]
else: mapper = operator.itemgetter(*indices)
# Get only list of actually imported fields
import_fields = filter(None, fields)
rows_to_import = self._read_file(record.file_type, record, options)
if options.get('headers'):
rows_to_import = itertools.islice(
rows_to_import, 1, None)
data = [
row for row in itertools.imap(mapper, rows_to_import)
# don't try inserting completely empty rows (e.g. from
# filtering out o2m fields)
if any(row)
]
return data, import_fields
def do(self, cr, uid, id, fields, options, dryrun=False, context=None):
""" Actual execution of the import
:param fields: import mapping: maps each column to a field,
``False`` for the columns to ignore
:type fields: list(str|bool)
:param dict options:
:param bool dryrun: performs all import operations (and
validations) but rollbacks writes, allows
getting as much errors as possible without
the risk of clobbering the database.
:returns: A list of errors. If the list is empty the import
executed fully and correctly. If the list is
non-empty it contains dicts with 3 keys ``type`` the
type of error (``error|warning``); ``message`` the
error message associated with the error (a string)
and ``record`` the data which failed to import (or
``false`` if that data isn't available or provided)
:rtype: list({type, message, record})
"""
cr.execute('SAVEPOINT import')
(record,) = self.browse(cr, uid, [id], context=context)
try:
data, import_fields = self._convert_import_data(
record, fields, options, context=context)
except ValueError, e:
return [{
'type': 'error',
'message': unicode(e),
'record': False,
}]
_logger.info('importing %d rows...', len(data))
import_result = self.pool[record.res_model].load(
cr, uid, import_fields, data, context=context)
_logger.info('done')
# If transaction aborted, RELEASE SAVEPOINT is going to raise
# an InternalError (ROLLBACK should work, maybe). Ignore that.
# TODO: to handle multiple errors, create savepoint around
# write and release it in case of write error (after
# adding error to errors array) => can keep on trying to
# import stuff, and rollback at the end if there is any
# error in the results.
try:
if dryrun:
cr.execute('ROLLBACK TO SAVEPOINT import')
else:
cr.execute('RELEASE SAVEPOINT import')
except psycopg2.InternalError:
pass
return import_result['messages']