"""
Serialize data to/from CSV
Since CSV deals only in string values, certain conventions must be
employed to represent other data types. The conventions used in this
serializer implementation are as follows:
- Boolean values are serialized as 'TRUE' and 'FALSE'
- The strings 'TRUE' and 'FALSE' are serialized as "'TRUE'" and "'FALSE'"
- None is serialized as 'NULL'
- The string 'NULL' is serialized as "'NULL'"
- Lists are serialized as comma separated items surrounded by brackets,
e.g. [foo, bar] becomes '[foo, bar]'
- Strings beginning with '[' and ending in ']' are serialized by being
wrapped in single quotes, e.g. '[foo, bar]' becomes "'[foo, bar]'"
See also:
http://docs.djangoproject.com/en/1.2/topics/serialization/
"""
import codecs
import csv
import re
import StringIO
from itertools import groupby
from operator import itemgetter
from django.core.serializers.python import Serializer as PythonSerializer
from django.core.serializers.python import Deserializer as PythonDeserializer
from django.utils.encoding import smart_unicode
class Serializer(PythonSerializer):
"""
Convert a queryset to CSV.
"""
internal_use_only = False
def end_serialization(self):
def process_item(item):
if isinstance(item, (list, tuple)):
item = process_m2m(item)
elif isinstance(item, bool):
item = str(item).upper()
elif isinstance(item, basestring):
if item in ('TRUE', 'FALSE', 'NULL') or _LIST_RE.match(item):
# Wrap these in quotes, so as not to be confused with
# builtin types when deserialized
item = "'%s'" % item
elif item is None:
item = 'NULL'
return smart_unicode(item)
def process_m2m(seq):
parts = []
for item in seq:
if isinstance(item, (list, tuple)):
parts.append(process_m2m(item))
else:
parts.append(process_item(item))
return '[%s]' % ', '.join(parts)
writer = UnicodeWriter(self.stream)
# Group objects by model and write out a header and rows for each.
# Multiple models can be present when invoking from the command
# line, e.g.: `python manage.py dumpdata --format csv auth`
for k, g in groupby(self.objects, key=itemgetter('model')):
write_header = True
for d in g:
# "flatten" the object. PK and model values come first,
# then field values. Flat is better than nested, right? :-)
pk, model, fields = d['pk'], d['model'], d['fields']
pk, model = smart_unicode(pk), smart_unicode(model)
row = [pk, model] + map(process_item, fields.values())
if write_header:
header = ['pk', 'model'] + fields.keys()
writer.writerow(header)
write_header = False
writer.writerow(row)
def getvalue(self):
if callable(getattr(self.stream, 'getvalue', None)):
return self.stream.getvalue()
_QUOTED_BOOL_NULL = """ 'TRUE' 'FALSE' 'NULL' "TRUE" "FALSE" "NULL" """.split()
# regular expressions used in deserialization
_LIST_PATTERN = r'\[(.*)\]'
_LIST_RE = re.compile(r'\A%s\Z' % _LIST_PATTERN)
_QUOTED_LIST_RE = re.compile(r"""
\A # beginning of string
(['"]) # quote char
%s # list
\1 # matching quote
\Z # end of string""" % _LIST_PATTERN, re.VERBOSE)
_SPLIT_RE = re.compile(r', *')
_NK_LIST_RE = re.compile(r"""
\A # beginning of string
\[ # opening bracket
[^]]+ # one or more non brackets
\] # closing bracket
(?:, *\[[^]]+\])* # zero or more of above, separated
# by a comma and optional spaces
\Z # end of string""", re.VERBOSE)
_NK_SPLIT_RE = re.compile(r"""
(?<=\]) # closing bracket (lookbehind)
, * # comma and optional spaces
(?=\[) # opening bracket (lookahead)""", re.VERBOSE)
def Deserializer(stream_or_string, **options):
"""
Deserialize a stream or string of CSV data.
"""
def process_item(item):
m = _LIST_RE.match(item)
if m:
contents = m.group(1)
if not contents:
item = []
else:
item = process_m2m(contents)
else:
if item == 'TRUE':
item = True
elif item == 'FALSE':
item = False
elif item == 'NULL':
item = None
elif (item in _QUOTED_BOOL_NULL or
_QUOTED_LIST_RE.match(item)):
item = item.strip('\'"')
return item
def process_m2m(contents):
li = []
if _NK_LIST_RE.match(contents):
for item in _NK_SPLIT_RE.split(contents):
li.append(process_item(item))
else:
li = _SPLIT_RE.split(contents)
return li
if isinstance(stream_or_string, basestring):
stream = StringIO.StringIO(stream_or_string)
else:
stream = stream_or_string
reader = UnicodeReader(stream)
header = next(reader) # first line must be a header
data = []
for row in reader:
# Need to account for the presence of multiple headers in
# the stream since serialized data can contain them.
if row[:2] == ['pk', 'model']:
# Not the best check. Perhaps csv.Sniffer.has_header
# would be better?
header = row
continue
d = dict(zip(header[:2], row[:2]))
d['fields'] = dict(zip(header[2:], map(process_item, row[2:])))
data.append(d)
for obj in PythonDeserializer(data, **options):
yield obj
# The classes below taken from http://docs.python.org/library/csv.html
class UTF8Recoder(object):
"""
Iterator that reads an encoded stream and reencodes the input to UTF-8
"""
def __init__(self, f, encoding):
self.reader = codecs.getreader(encoding)(f)
def __iter__(self):
return self
def next(self):
return self.reader.next().encode('utf-8')
class UnicodeReader(object):
"""
A CSV reader which will iterate over lines in the CSV file "f",
which is encoded in the given encoding.
"""
def __init__(self, f, dialect=csv.excel, encoding='utf-8', **kwds):
f = UTF8Recoder(f, encoding)
self.reader = csv.reader(f, dialect=dialect, **kwds)
def next(self):
row = self.reader.next()
return [unicode(s, 'utf-8') for s in row]
def __iter__(self):
return self
class UnicodeWriter(object):
"""
A CSV writer which will write rows to CSV file "f",
which is encoded in the given encoding.
"""
def __init__(self, f, dialect=csv.excel, encoding='utf-8', **kwds):
# Redirect output to a queue
self.queue = StringIO.StringIO()
self.writer = csv.writer(self.queue, dialect=dialect, **kwds)
self.stream = f
self.encoder = codecs.getincrementalencoder(encoding)()
def writerow(self, row):
self.writer.writerow([s.encode('utf-8') for s in row])
# Fetch UTF-8 output from the queue ...
data = self.queue.getvalue()
data = data.decode('utf-8')
# ... and reencode it into the target encoding
data = self.encoder.encode(data)
# write to the target stream
self.stream.write(data)
# empty queue
self.queue.truncate(0)
def writerows(self, rows):
for row in rows:
self.writerow(row)