r"""

CSV parsing and writing.

This module provides classes that assist in the reading and writing

of Comma Separated Value (CSV) files, and implements the interface

described by PEP 305. Although many CSV files are simple to parse,

the format is not formally defined by a stable specification and

is subtle enough that parsing lines of a CSV file with something

like line.split(",") is bound to fail. The module supports three

basic APIs: reading, writing, and registration of dialects.

DIALECT REGISTRATION:

Readers and writers support a dialect argument, which is a convenient

handle on a group of settings. When the dialect argument is a string,

it identifies one of the dialects previously registered with the module.

If it is a class or instance, the attributes of the argument are used as

the settings for the reader or writer:

class excel:

delimiter = ','

quotechar = '"'

escapechar = None

doublequote = True

skipinitialspace = False

lineterminator = '\r\n'

quoting = QUOTE_MINIMAL

SETTINGS:

* quotechar - specifies a one-character string to use as the

quoting character. It defaults to '"'.

* delimiter - specifies a one-character string to use as the

field separator. It defaults to ','.

* skipinitialspace - specifies how to interpret spaces which

immediately follow a delimiter. It defaults to False, which

means that spaces immediately following a delimiter is part

of the following field.

* lineterminator - specifies the character sequence which should

terminate rows.

* quoting - controls when quotes should be generated by the writer.

It can take on any of the following module constants:

csv.QUOTE_MINIMAL means only when required, for example, when a

field contains either the quotechar or the delimiter

csv.QUOTE_ALL means that quotes are always placed around fields.

csv.QUOTE_NONNUMERIC means that quotes are always placed around

fields which do not parse as integers or floating-point

numbers.

csv.QUOTE_STRINGS means that quotes are always placed around

fields which are strings. Note that the Python value None

is not a string.

csv.QUOTE_NOTNULL means that quotes are only placed around fields

that are not the Python value None.

csv.QUOTE_NONE means that quotes are never placed around fields.

* escapechar - specifies a one-character string used to escape

the delimiter when quoting is set to QUOTE_NONE.

* doublequote - controls the handling of quotes inside fields. When

True, two consecutive quotes are interpreted as one during read,

and when writing, each quote character embedded in the data is

written as two quotes

"""

import types

from _csv import Error, writer, reader, register_dialect, \

unregister_dialect, get_dialect, list_dialects, \

field_size_limit, \

QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \

QUOTE_STRINGS, QUOTE_NOTNULL

from _csv import Dialect as _Dialect

from io import StringIO

__all__ = ["QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE",

"QUOTE_STRINGS", "QUOTE_NOTNULL",

"Error", "Dialect", "excel", "excel_tab",

"field_size_limit", "reader", "writer",

"register_dialect", "get_dialect", "list_dialects", "Sniffer",

"unregister_dialect", "DictReader", "DictWriter",

"unix_dialect"]

class Dialect:

"""Describe a CSV dialect.

This must be subclassed (see csv.excel). Valid attributes are:

delimiter, quotechar, escapechar, doublequote, skipinitialspace,

lineterminator, quoting.

"""

_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

self._validate()

def _validate(self):

try:

_Dialect(self)

except TypeError as e:

# Re-raise to get a traceback showing more user code.

raise Error(str(e)) from None

class excel(Dialect):

"""Describe the usual properties of Excel-generated CSV files."""

delimiter = ','

quotechar = '"'

doublequote = True

skipinitialspace = False

lineterminator = '\r\n'

quoting = QUOTE_MINIMAL

register_dialect("excel", excel)

class excel_tab(excel):

"""Describe the usual properties of Excel-generated TAB-delimited files."""

delimiter = '\t'

register_dialect("excel-tab", excel_tab)

class unix_dialect(Dialect):

"""Describe the usual properties of Unix-generated CSV files."""

delimiter = ','

quotechar = '"'

doublequote = True

skipinitialspace = False

lineterminator = '\n'

quoting = QUOTE_ALL

register_dialect("unix", unix_dialect)

class DictReader:

def __init__(self, f, fieldnames=None, restkey=None, restval=None,

dialect="excel", *args, **kwds):

if fieldnames is not None and iter(fieldnames) is fieldnames:

fieldnames = list(fieldnames)

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, **kwds)

self.dialect = dialect

self.line_num = 0

def __iter__(self):

return self

@property

def fieldnames(self):

if self._fieldnames is None:

try:

self._fieldnames = next(self.reader)

except StopIteration:

pass

self.line_num = self.reader.line_num

return self._fieldnames

@fieldnames.setter

def fieldnames(self, value):

self._fieldnames = value

def __next__(self):

if self.line_num == 0:

# Used only for its side effect.

self.fieldnames

row = next(self.reader)

self.line_num = self.reader.line_num

# 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 = next(self.reader)

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_getitem__ = classmethod(types.GenericAlias)

class DictWriter:

def __init__(self, f, fieldnames, restval="", extrasaction="raise",

dialect="excel", *args, **kwds):

if fieldnames is not None and iter(fieldnames) is fieldnames:

fieldnames = list(fieldnames)

self.fieldnames = fieldnames # list of keys for the dict

self.restval = restval # for writing short dicts

extrasaction = extrasaction.lower()

if extrasaction not in ("raise", "ignore"):

raise ValueError("extrasaction (%s) must be 'raise' or 'ignore'"

% extrasaction)

self.extrasaction = extrasaction

self.writer = writer(f, dialect, *args, **kwds)

def writeheader(self):

header = dict(zip(self.fieldnames, self.fieldnames))

return self.writerow(header)

def _dict_to_list(self, rowdict):

if self.extrasaction == "raise":

wrong_fields = rowdict.keys() - self.fieldnames

if wrong_fields:

raise ValueError("dict contains fields not in fieldnames: "

+ ", ".join([repr(x) for x in wrong_fields]))

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):

return self.writer.writerows(map(self._dict_to_list, rowdicts))

__class_getitem__ = classmethod(types.GenericAlias)

class Sniffer:

'''

"Sniffs" the format of a CSV file (i.e. delimiter, quotechar)

Returns a Dialect object.

'''

# Characters which can be guessed as a delimiter if the delimiters

# argument is not specified.

_delimiter_candidates = [c for c in map(chr, range(128))

if not c.isalnum()]

def __init__(self):

# in case there is more than one possible delimiter

self.preferred = [',', '\t', ';', ' ', ':']

def sniff(self, sample, delimiters=None):

"""

Analyze the sample and return a Dialect subclass reflecting the

parameters found. If the optional delimiters parameter is

given, it is interpreted as a string containing possible valid

delimiter characters. Raises Error if the dialect cannot be

determined.

The dialect is guessed by parsing the sample with every

plausible combination of delimiter, quotechar and escapechar,

and choosing the combination which splits the sample into rows

with the most consistent number of fields.

A large sample is parsed incrementally: first only its

beginning, then, after eliminating the combinations which are

clearly worse than the leader, a several times larger part,

and so on.

If several combinations fit the sample equally well, the

delimiters listed in the preferred attribute are preferred, in

that order, no matter how many times each of them occurs.

"""

import re

from collections import defaultdict

if self._parses_as_single_column(sample):

# There is no delimiter to find; any combination could

# only find a bogus one inside the quoted fields.

raise Error("Could not determine delimiter")

chars = set(sample)

if delimiters is None:

delimiters = self._delimiter_candidates

delimiters = [d for d in delimiters

if d in chars and d not in '\r\n"\'\\']

# Combinations to try, numbered by preference for breaking

# ties. The unquoted combinations are parsed from the start;

# the rest stay dormant until the quote character occurs at

# the start of a field (see _split_dormant).

groups = defaultdict(list)

order = 0

# Only '\\' is tried as an escape character: others are not

# seen in the wild.

for escapechar in ('', '\\') if '\\' in chars else ('',):

for quotechar in '"', "'", '':

if quotechar and quotechar not in chars:

continue

for delimiter in delimiters:

groups[quotechar].append(

(order, delimiter, quotechar, escapechar))

order += 1

active = groups.pop('', [])

# Only non-empty groups were created; a plain dict cannot

# grow one by accident.

dormant = dict(groups)

# The initial window should cover the minimal number of rows

# required for elimination (see _eliminate_worse) at a typical

# line length, so that the first round can already eliminate.

window = 2000

# A line with its line break: '\r', '\n' or '\r\n' (the

# reader treats other line boundary characters as ordinary

# data, but does not support a bare '\r' inside a chunk).

# The \z alternative produces one final empty match.

line_re = re.compile(r'[^\r\n]*(?:\r\n|[\r\n]|\z)')

parsed = []

lines = []

first_round = True

while active or dormant:

end = min(window, len(sample))

part = sample[:end]

lines = line_re.findall(part)

del lines[-1]

cut = not part.endswith(('\r', '\n'))

for quotechar in list(dormant):

activated, still = self._split_dormant(

part, quotechar, dormant[quotechar])

active += activated

if still:

dormant[quotechar] = still

else:

del dormant[quotechar]

parsed = [(combo, self._try_dialect(lines, cut, *combo[1:]))

for combo in active]

if end == len(sample):

break

active = self._eliminate_worse(parsed, not first_round)

first_round = False

if len(active) <= 3:

# Quoted data most often leaves three survivors: the

# true dialect, its equally consistent unquoted shadow,

# and one accident. Parsing the whole sample with them

# is cheaper than another elimination round.

window = len(sample)

else:

# Too small a factor would increase the total

# re-parsing cost, too large -- the cost of the next

# round if this one did not eliminate enough.

window *= 4

best = None

best_score = None

for combo, rows in sorted(parsed):

if rows is None:

continue

_, delimiter, quotechar, escapechar = combo

nfields, share = self._modal_share(rows)

if nfields < 2:

# The delimiter does not delimit anything.

continue

try:

preference = -self.preferred.index(delimiter)

except ValueError:

preference = -len(self.preferred)

# A successful quoted parse is direct evidence; the preferred

# delimiters list is only a nudge.

score = (share, len(rows), bool(quotechar), preference)

if best_score is None or score > best_score:

best_score = score

best = combo[1:]

if best is None:

raise Error("Could not determine delimiter")

delimiter, quotechar, escapechar = best

doublequote = self._detect_doublequote(lines, *best)

skipinitialspace = self._detect_skipinitialspace(lines, *best,

doublequote)

class dialect(Dialect):

_name = "sniffed"

lineterminator = '\r\n'

quoting = QUOTE_MINIMAL

dialect.delimiter = delimiter

# _csv.reader won't accept a quotechar of ''

dialect.quotechar = quotechar or '"'

dialect.escapechar = escapechar or None

dialect.doublequote = doublequote

dialect.skipinitialspace = skipinitialspace

return dialect

def _parses_as_single_column(self, sample):

"""

True if the whole sample parses as a single column of quoted

fields (the last one may be cut off in the middle), so there

is no delimiter to find.

"""

import re

for q in '"', "'":

if q in sample:

row_re = (fr' *+{q}(?:[^{q}]|{q}{q})*+'

fr'(?:{q} *+(?:[\r\n]++|\z)|\z)')

if re.fullmatch(fr'(?:{row_re})++', sample):

return True

return False

def _split_dormant(self, part, quotechar, combos):

"""

Split the dormant combinations into those ready for trial

parsing and the rest.

A combination is ready when its quote character occurs in

*part* at the start of a field, i.e. at the start of a line or

after its delimiter; until then parsing would not differ from

the unquoted variant. Spaces before the quote are allowed even

for the space delimiter: a false activation only costs a trial

parse.

"""

import re

remaining = {combo[1] for combo in combos}

found = set()

pos = 0

while remaining:

# Include only the delimiters not found yet, so that the

# search skips over the found ones; the compiled patterns

# come from the re cache.

cls = re.escape(''.join(sorted(remaining)))

m = re.compile(fr'(?:^|([\r\n{cls}]))'

fr' *{quotechar}').search(part, pos)

if m is None:

break

pre = m[1]

if pre is None or pre in '\r\n':

# A quote at the start of a line starts a field for

# every delimiter.

found |= remaining

break

found.add(pre)

remaining.discard(pre)

pos = m.end()

activated = [combo for combo in combos if combo[1] in found]

still_dormant = [combo for combo in combos if combo[1] not in found]

return activated, still_dormant

def _make_reader(self, lines, delimiter, quotechar, escapechar,

doublequote=True, skipinitialspace=None):

"""

Create a reader for trial parsing. quotechar '' means no

quoting and escapechar '' means no escape character.

"""

if skipinitialspace is None:

# Be lenient to spaces after a delimiter, unless the

# delimiter is a space itself.

skipinitialspace = delimiter != ' '

return reader(lines, delimiter=delimiter,

quotechar=quotechar or '"',

quoting=QUOTE_MINIMAL if quotechar else QUOTE_NONE,

escapechar=escapechar or None,

doublequote=doublequote,

skipinitialspace=skipinitialspace,

strict=True)

def _try_dialect(self, lines, cut, delimiter, quotechar, escapechar):

"""

Parse the sample, pre-split into *lines*, and return the list

of the number of fields in every parsed row, or None if not a

single row was parsed.

If the sample cannot be parsed to the end (for example it is

cut off in the middle of a quoted field, or the combination

does not fit the sample), the rows parsed so far are counted.

The last row is not counted if *cut* is true: the sample can

be cut off in the middle of it.

"""

rows = []

try:

rows.extend(map(len, self._make_reader(lines, delimiter,

quotechar, escapechar)))

except Error:

# The row which failed to parse is not counted.

pass

else:

if cut and len(rows) > 1:

rows.pop()

if 0 in rows:

# Blank lines produce empty rows.

rows = [nfields for nfields in rows if nfields]

return rows or None

def _eliminate_worse(self, parsed, judge_hopeless):

"""

Return the combinations from *parsed* (a list of (combination,

rows) pairs) without those which are clearly worse than the

leader. Combinations with too few parsed rows (e.g. if the

parsed part ends in the middle of a large quoted field) are

not judged yet.

If *judge_hopeless* is false, keep the combinations whose

delimiter does not delimit anything. Unlike the comparison

with the leader, which self-normalizes when the parsed part is

not representative, this verdict is absolute and irreversible,

so it is not trusted to the first part, which covers the least

representative beginning of the sample (titles, headers,

preamble).

"""

# Judging a combination by fewer rows is too noisy.

min_rows = 16

hopeless = set()

scores = {}

for combo, rows in parsed:

if rows is not None and len(rows) >= min_rows:

nfields, share = self._modal_share(rows)

if nfields < 2:

if judge_hopeless:

hopeless.add(combo)

else:

scores[combo] = share

threshold = max(scores.values(), default=0.0) - 0.1

return [combo for combo, _ in parsed

if combo not in hopeless

and scores.get(combo, threshold) >= threshold]

def _modal_share(self, rows):

"""

The most common number of fields in a row and its share of all

rows. Prefer the smaller number of fields in the case of a

tie: a candidate delimiter which delimits only half of the rows

is not convincing.

"""

from collections import Counter

counts = Counter(rows)

nfields = max(counts, key=lambda n: (counts[n], -n))

return nfields, counts[nfields] / len(rows)

def _detect_doublequote(self, lines, delimiter, quotechar, escapechar):

"""

True if a doubled quote character represents a single quote

character in the sample: interpreting it so changes the result

of parsing.

"""

if not quotechar or not any(quotechar * 2 in line

for line in lines):

return False

readers = [self._make_reader(

lines, delimiter, quotechar, escapechar,

doublequote=doublequote)

for doublequote in (False, True)]

while True:

rows = []

for rdr in readers:

try:

rows.append(next(rdr))

except (StopIteration, Error):

# Ending cleanly and failing are equivalent here:

# after equal rows both readers are at the same

# position, so they cannot end for different

# reasons.

rows.append(None)

if rows[0] != rows[1]:

return True

if rows == [None, None]:

return False

def _detect_skipinitialspace(self, lines, delimiter, quotechar,

escapechar, doublequote):

"""

True only if every field following a delimiter starts with

a space.

"""

skipinitialspace = False

try:

for row in self._make_reader(lines, delimiter, quotechar,

escapechar,

doublequote=doublequote,

skipinitialspace=False):

for field in row[1:]:

if not field.startswith(' '):

return False

skipinitialspace = True

except Error:

pass

return skipinitialspace

def has_header(self, sample):

# 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.

rdr = reader(StringIO(sample), self.sniff(sample))

header = next(rdr) # assume first row is header

columns = len(header)

columnTypes = {}

for i in range(columns): columnTypes[i] = None

checked = 0

for row in rdr:

# 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 list(columnTypes.keys()):

thisType = complex

try:

thisType(row[col])

except (ValueError, OverflowError):

# 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 isinstance(colType, int): # it's a length

if len(header[col]) != colType:

hasHeader += 1

else:

hasHeader -= 1

else: # attempt typecast

try:

colType(header[col])

except (ValueError, TypeError):

hasHeader += 1

else:

hasHeader -= 1

return hasHeader > 0

def __getattr__(name):

if name == "__version__":

from warnings import _deprecated

_deprecated("__version__", remove=(3, 20))

return "1.0" # Do not change

raise AttributeError(f"module {__name__!r} has no attribute {name!r}")