1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
|
"""
csv.py - read/write/investigate CSV files
"""
import re
from _csv import Error, __version__, writer, reader, register_dialect, \
unregister_dialect, get_dialect, list_dialects, \
QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \
__doc__
__all__ = [ "QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE",
"Error", "Dialect", "excel", "excel_tab", "reader", "writer",
"register_dialect", "get_dialect", "list_dialects", "Sniffer",
"unregister_dialect", "__version__", "DictReader", "DictWriter" ]
class Dialect:
_name = ""
_valid = False
# placeholders
delimiter = None
quotechar = None
escapechar = None
doublequote = None
skipinitialspace = None
lineterminator = None
quoting = None
def __init__(self):
if self.__class__ != Dialect:
self._valid = True
errors = self._validate()
if errors != []:
raise Error, "Dialect did not validate: %s" % ", ".join(errors)
def _validate(self):
errors = []
if not self._valid:
errors.append("can't directly instantiate Dialect class")
if self.delimiter is None:
errors.append("delimiter character not set")
elif (not isinstance(self.delimiter, str) or
len(self.delimiter) > 1):
errors.append("delimiter must be one-character string")
if self.quotechar is None:
if self.quoting != QUOTE_NONE:
errors.append("quotechar not set")
elif (not isinstance(self.quotechar, str) or
len(self.quotechar) > 1):
errors.append("quotechar must be one-character string")
if self.lineterminator is None:
errors.append("lineterminator not set")
elif not isinstance(self.lineterminator, str):
errors.append("lineterminator must be a string")
if self.doublequote not in (True, False):
errors.append("doublequote parameter must be True or False")
if self.skipinitialspace not in (True, False):
errors.append("skipinitialspace parameter must be True or False")
if self.quoting is None:
errors.append("quoting parameter not set")
if self.quoting is QUOTE_NONE:
if (not isinstance(self.escapechar, (unicode, str)) or
len(self.escapechar) > 1):
errors.append("escapechar must be a one-character string or unicode object")
return errors
class excel(Dialect):
delimiter = ','
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\r\n'
quoting = QUOTE_MINIMAL
register_dialect("excel", excel)
class excel_tab(excel):
delimiter = '\t'
register_dialect("excel-tab", excel_tab)
class DictReader:
def __init__(self, f, fieldnames, restkey=None, restval=None,
dialect="excel", *args):
self.fieldnames = fieldnames # list of keys for the dict
self.restkey = restkey # key to catch long rows
self.restval = restval # default value for short rows
self.reader = reader(f, dialect, *args)
def __iter__(self):
return self
def next(self):
row = self.reader.next()
# unlike the basic reader, we prefer not to return blanks,
# because we will typically wind up with a dict full of None
# values
while row == []:
row = self.reader.next()
d = dict(zip(self.fieldnames, row))
lf = len(self.fieldnames)
lr = len(row)
if lf < lr:
d[self.restkey] = row[lf:]
elif lf > lr:
for key in self.fieldnames[lr:]:
d[key] = self.restval
return d
class DictWriter:
def __init__(self, f, fieldnames, restval="", extrasaction="raise",
dialect="excel", *args):
self.fieldnames = fieldnames # list of keys for the dict
self.restval = restval # for writing short dicts
if extrasaction.lower() not in ("raise", "ignore"):
raise ValueError, \
("extrasaction (%s) must be 'raise' or 'ignore'" %
extrasaction)
self.extrasaction = extrasaction
self.writer = writer(f, dialect, *args)
def _dict_to_list(self, rowdict):
if self.extrasaction == "raise":
for k in rowdict.keys():
if k not in self.fieldnames:
raise ValueError, "dict contains fields not in fieldnames"
return [rowdict.get(key, self.restval) for key in self.fieldnames]
def writerow(self, rowdict):
return self.writer.writerow(self._dict_to_list(rowdict))
def writerows(self, rowdicts):
rows = []
for rowdict in rowdicts:
rows.append(self._dict_to_list(rowdict))
return self.writer.writerows(rows)
class Sniffer:
'''
"Sniffs" the format of a CSV file (i.e. delimiter, quotechar)
Returns a csv.Dialect object.
'''
def __init__(self, sample = 16 * 1024):
# in case there is more than one possible delimiter
self.preferred = [',', '\t', ';', ' ', ':']
# amount of data (in bytes) to sample
self.sample = sample
def sniff(self, fileobj):
"""
Takes a file-like object and returns a dialect (or None)
"""
self.fileobj = fileobj
data = fileobj.read(self.sample)
quotechar, delimiter, skipinitialspace = \
self._guessQuoteAndDelimiter(data)
if delimiter is None:
delimiter, skipinitialspace = self._guessDelimiter(data)
class SniffedDialect(Dialect):
_name = "sniffed"
lineterminator = '\r\n'
quoting = QUOTE_MINIMAL
# escapechar = ''
doublequote = False
SniffedDialect.delimiter = delimiter
SniffedDialect.quotechar = quotechar
SniffedDialect.skipinitialspace = skipinitialspace
self.dialect = SniffedDialect
return self.dialect
def hasHeaders(self):
return self._hasHeaders(self.fileobj, self.dialect)
def register_dialect(self, name='sniffed'):
register_dialect(name, self.dialect)
def _guessQuoteAndDelimiter(self, data):
"""
Looks for text enclosed between two identical quotes
(the probable quotechar) which are preceded and followed
by the same character (the probable delimiter).
For example:
,'some text',
The quote with the most wins, same with the delimiter.
If there is no quotechar the delimiter can't be determined
this way.
"""
matches = []
for restr in ('(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?P=delim)', # ,".*?",
'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?P<delim>[^\w\n"\'])(?P<space> ?)', # ".*?",
'(?P<delim>>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?:$|\n)', # ,".*?"
'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?:$|\n)'): # ".*?" (no delim, no space)
regexp = re.compile(restr, re.S | re.M)
matches = regexp.findall(data)
if matches:
break
if not matches:
return ('', None, 0) # (quotechar, delimiter, skipinitialspace)
quotes = {}
delims = {}
spaces = 0
for m in matches:
n = regexp.groupindex['quote'] - 1
key = m[n]
if key:
quotes[key] = quotes.get(key, 0) + 1
try:
n = regexp.groupindex['delim'] - 1
key = m[n]
except KeyError:
continue
if key:
delims[key] = delims.get(key, 0) + 1
try:
n = regexp.groupindex['space'] - 1
except KeyError:
continue
if m[n]:
spaces += 1
quotechar = reduce(lambda a, b, quotes = quotes:
(quotes[a] > quotes[b]) and a or b, quotes.keys())
if delims:
delim = reduce(lambda a, b, delims = delims:
(delims[a] > delims[b]) and a or b, delims.keys())
skipinitialspace = delims[delim] == spaces
if delim == '\n': # most likely a file with a single column
delim = ''
else:
# there is *no* delimiter, it's a single column of quoted data
delim = ''
skipinitialspace = 0
return (quotechar, delim, skipinitialspace)
def _guessDelimiter(self, data):
"""
The delimiter /should/ occur the same number of times on
each row. However, due to malformed data, it may not. We don't want
an all or nothing approach, so we allow for small variations in this
number.
1) build a table of the frequency of each character on every line.
2) build a table of freqencies of this frequency (meta-frequency?),
e.g. 'x occurred 5 times in 10 rows, 6 times in 1000 rows,
7 times in 2 rows'
3) use the mode of the meta-frequency to determine the /expected/
frequency for that character
4) find out how often the character actually meets that goal
5) the character that best meets its goal is the delimiter
For performance reasons, the data is evaluated in chunks, so it can
try and evaluate the smallest portion of the data possible, evaluating
additional chunks as necessary.
"""
data = filter(None, data.split('\n'))
ascii = [chr(c) for c in range(127)] # 7-bit ASCII
# build frequency tables
chunkLength = min(10, len(data))
iteration = 0
charFrequency = {}
modes = {}
delims = {}
start, end = 0, min(chunkLength, len(data))
while start < len(data):
iteration += 1
for line in data[start:end]:
for char in ascii:
metafrequency = charFrequency.get(char, {})
# must count even if frequency is 0
freq = line.strip().count(char)
# value is the mode
metafrequency[freq] = metafrequency.get(freq, 0) + 1
charFrequency[char] = metafrequency
for char in charFrequency.keys():
items = charFrequency[char].items()
if len(items) == 1 and items[0][0] == 0:
continue
# get the mode of the frequencies
if len(items) > 1:
modes[char] = reduce(lambda a, b: a[1] > b[1] and a or b,
items)
# adjust the mode - subtract the sum of all
# other frequencies
items.remove(modes[char])
modes[char] = (modes[char][0], modes[char][1]
- reduce(lambda a, b: (0, a[1] + b[1]),
items)[1])
else:
modes[char] = items[0]
# build a list of possible delimiters
modeList = modes.items()
total = float(chunkLength * iteration)
# (rows of consistent data) / (number of rows) = 100%
consistency = 1.0
# minimum consistency threshold
threshold = 0.9
while len(delims) == 0 and consistency >= threshold:
for k, v in modeList:
if v[0] > 0 and v[1] > 0:
if (v[1]/total) >= consistency:
delims[k] = v
consistency -= 0.01
if len(delims) == 1:
delim = delims.keys()[0]
skipinitialspace = (data[0].count(delim) ==
data[0].count("%c " % delim))
return (delim, skipinitialspace)
# analyze another chunkLength lines
start = end
end += chunkLength
if not delims:
return ('', 0)
# if there's more than one, fall back to a 'preferred' list
if len(delims) > 1:
for d in self.preferred:
if d in delims.keys():
skipinitialspace = (data[0].count(d) ==
data[0].count("%c " % d))
return (d, skipinitialspace)
# finally, just return the first damn character in the list
delim = delims.keys()[0]
skipinitialspace = (data[0].count(delim) ==
data[0].count("%c " % delim))
return (delim, skipinitialspace)
def _hasHeaders(self, fileobj, dialect):
# Creates a dictionary of types of data in each column. If any
# column is of a single type (say, integers), *except* for the first
# row, then the first row is presumed to be labels. If the type
# can't be determined, it is assumed to be a string in which case
# the length of the string is the determining factor: if all of the
# rows except for the first are the same length, it's a header.
# Finally, a 'vote' is taken at the end for each column, adding or
# subtracting from the likelihood of the first row being a header.
def seval(item):
"""
Strips parens from item prior to calling eval in an
attempt to make it safer
"""
return eval(item.replace('(', '').replace(')', ''))
# rewind the fileobj - this might not work for some file-like
# objects...
fileobj.seek(0)
r = csv.reader(fileobj,
delimiter=dialect.delimiter,
quotechar=dialect.quotechar,
skipinitialspace=dialect.skipinitialspace)
header = r.next() # assume first row is header
columns = len(header)
columnTypes = {}
for i in range(columns): columnTypes[i] = None
checked = 0
for row in r:
# arbitrary number of rows to check, to keep it sane
if checked > 20:
break
checked += 1
if len(row) != columns:
continue # skip rows that have irregular number of columns
for col in columnTypes.keys():
try:
try:
# is it a built-in type (besides string)?
thisType = type(seval(row[col]))
except OverflowError:
# a long int?
thisType = type(seval(row[col] + 'L'))
thisType = type(0) # treat long ints as int
except:
# fallback to length of string
thisType = len(row[col])
if thisType != columnTypes[col]:
if columnTypes[col] is None: # add new column type
columnTypes[col] = thisType
else:
# type is inconsistent, remove column from
# consideration
del columnTypes[col]
# finally, compare results against first row and "vote"
# on whether it's a header
hasHeader = 0
for col, colType in columnTypes.items():
if type(colType) == type(0): # it's a length
if len(header[col]) != colType:
hasHeader += 1
else:
hasHeader -= 1
else: # attempt typecast
try:
eval("%s(%s)" % (colType.__name__, header[col]))
except:
hasHeader += 1
else:
hasHeader -= 1
return hasHeader > 0
|