FM / python3.9

/usr/lib64/python3.9

Name	Size	Mode	Actions
asyncio/	-	0755	rm
collections/	-	0755	rm
concurrent/	-	0755	rm
config-3.9-x86_64-linux-gnu/	-	0755	rm
ctypes/	-	0755	rm
curses/	-	0755	rm
dbm/	-	0755	rm
distutils/	-	0755	rm
email/	-	0755	rm
encodings/	-	0755	rm
ensurepip/	-	0755	rm
html/	-	0755	rm
http/	-	0755	rm
importlib/	-	0755	rm
json/	-	0755	rm
lib-dynload/	-	0755	rm
lib2to3/	-	0755	rm
logging/	-	0755	rm
multiprocessing/	-	0755	rm
pydoc_data/	-	0755	rm
site-packages/	-	0755	rm
sqlite3/	-	0755	rm
unittest/	-	0755	rm
urllib/	-	0755	rm
venv/	-	0755	rm
wsgiref/	-	0755	rm
xml/	-	0755	rm
xmlrpc/	-	0755	rm
zoneinfo/	-	0755	rm
__pycache__/	-	0755	rm
abc.py	4920	0644	edit dl rm
aifc.py	32605	0644	edit dl rm
antigravity.py	500	0644	edit dl rm
argparse.py	98119	0644	edit dl rm
ast.py	56256	0644	edit dl rm
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asyncore.py	20102	0644	edit dl rm
base64.py	19859	0755	edit dl rm
bdb.py	31389	0644	edit dl rm
binhex.py	14784	0644	edit dl rm
bisect.py	2350	0644	edit dl rm
bz2.py	12447	0644	edit dl rm
calendar.py	24832	0644	edit dl rm
cgi.py	33932	0755	edit dl rm
cgitb.py	12096	0644	edit dl rm
chunk.py	5435	0644	edit dl rm
cmd.py	14860	0644	edit dl rm
code.py	10622	0644	edit dl rm
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codeop.py	6326	0644	edit dl rm
colorsys.py	4064	0644	edit dl rm
compileall.py	20105	0644	edit dl rm
configparser.py	54584	0644	edit dl rm
contextlib.py	24624	0644	edit dl rm
contextvars.py	129	0644	edit dl rm
copy.py	8650	0644	edit dl rm
copyreg.py	7274	0644	edit dl rm
cProfile.py	6345	0755	edit dl rm
crypt.py	3819	0644	edit dl rm
csv.py	16144	0644	edit dl rm
dataclasses.py	49586	0644	edit dl rm
datetime.py	89177	0644	edit dl rm
decimal.py	320	0644	edit dl rm
difflib.py	83307	0644	edit dl rm
dis.py	20570	0644	edit dl rm
doctest.py	104568	0644	edit dl rm
enum.py	39440	0644	edit dl rm
filecmp.py	10024	0644	edit dl rm
fileinput.py	14791	0644	edit dl rm
fnmatch.py	6004	0644	edit dl rm
formatter.py	15143	0644	edit dl rm
fractions.py	24323	0644	edit dl rm
ftplib.py	35496	0644	edit dl rm
functools.py	38881	0644	edit dl rm
genericpath.py	5246	0644	edit dl rm
getopt.py	7489	0644	edit dl rm
getpass.py	5990	0644	edit dl rm
gettext.py	27266	0644	edit dl rm
glob.py	5823	0644	edit dl rm
graphlib.py	9573	0644	edit dl rm
gzip.py	21772	0644	edit dl rm
hashlib.py	8069	0644	edit dl rm
heapq.py	22877	0644	edit dl rm
hmac.py	8043	0644	edit dl rm
imaplib.py	55256	0644	edit dl rm
imghdr.py	3808	0644	edit dl rm
imp.py	10536	0644	edit dl rm
inspect.py	118235	0644	edit dl rm
io.py	3541	0644	edit dl rm
ipaddress.py	80924	0644	edit dl rm
keyword.py	1047	0644	edit dl rm
LICENSE.txt	13937	0644	edit dl rm
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locale.py	78271	0644	edit dl rm
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modulefinder.py	24401	0644	edit dl rm
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numbers.py	10338	0644	edit dl rm
opcode.py	5660	0644	edit dl rm
operator.py	10751	0644	edit dl rm
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os.py	39065	0644	edit dl rm
pathlib.py	51134	0644	edit dl rm
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pickle.py	64920	0644	edit dl rm
pickletools.py	93486	0644	edit dl rm
pipes.py	8916	0644	edit dl rm
pkgutil.py	24276	0644	edit dl rm
platform.py	40601	0755	edit dl rm
plistlib.py	28248	0644	edit dl rm
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profile.py	22881	0755	edit dl rm
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pydoc.py	109599	0755	edit dl rm
py_compile.py	8203	0644	edit dl rm
queue.py	11496	0644	edit dl rm
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random.py	31484	0644	edit dl rm
re.py	15861	0644	edit dl rm
reprlib.py	5267	0644	edit dl rm
rlcompleter.py	7648	0644	edit dl rm
runpy.py	13084	0644	edit dl rm
sched.py	6442	0644	edit dl rm
secrets.py	2036	0644	edit dl rm
selectors.py	19536	0644	edit dl rm
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signal.py	2438	0644	edit dl rm
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socket.py	36915	0644	edit dl rm
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ssl.py	52622	0644	edit dl rm
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string.py	10566	0644	edit dl rm
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struct.py	257	0644	edit dl rm
subprocess.py	83564	0644	edit dl rm
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symbol.py	2281	0644	edit dl rm
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sysconfig.py	25557	0644	edit dl rm
tabnanny.py	11406	0755	edit dl rm
tarfile.py	112939	0755	edit dl rm
telnetlib.py	23254	0644	edit dl rm
tempfile.py	27963	0644	edit dl rm
textwrap.py	19407	0644	edit dl rm
this.py	1003	0644	edit dl rm
threading.py	54176	0644	edit dl rm
timeit.py	13480	0755	edit dl rm
token.py	2368	0644	edit dl rm
tokenize.py	25883	0644	edit dl rm
trace.py	29207	0755	edit dl rm
traceback.py	24660	0644	edit dl rm
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tty.py	879	0644	edit dl rm
types.py	9785	0644	edit dl rm
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uu.py	7277	0644	edit dl rm
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warnings.py	19688	0644	edit dl rm
wave.py	18004	0644	edit dl rm
weakref.py	21560	0644	edit dl rm
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__future__.py	5147	0644	edit dl rm
__phello__.foo.py	64	0644	edit dl rm

Edit: /usr/lib64/python3.9/csv.py (16144B)

"""
csv.py - read/write/investigate CSV files
"""

import re
from _csv import Error, __version__, writer, reader, register_dialect, \
                 unregister_dialect, get_dialect, list_dialects, \
                 field_size_limit, \
                 QUOTE_MINIMAL, QUOTE_ALL, QUOTE_NONNUMERIC, QUOTE_NONE, \
                 __doc__
from _csv import Dialect as _Dialect

from io import StringIO

__all__ = ["QUOTE_MINIMAL", "QUOTE_ALL", "QUOTE_NONNUMERIC", "QUOTE_NONE",
           "Error", "Dialect", "__doc__", "excel", "excel_tab",
           "field_size_limit", "reader", "writer",
           "register_dialect", "get_dialect", "list_dialects", "Sniffer",
           "unregister_dialect", "__version__", "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:
            # We do this for compatibility with py2.3
            raise Error(str(e))

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):
        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 DictWriter:
    def __init__(self, f, fieldnames, restval="", extrasaction="raise",
                 dialect="excel", *args, **kwds):
        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, **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))

# Guard Sniffer's type checking against builds that exclude complex()
try:
    complex
except NameError:
    complex = float

class Sniffer:
    '''
    "Sniffs" the format of a CSV file (i.e. delimiter, quotechar)
    Returns a Dialect object.
    '''
    def __init__(self):
        # in case there is more than one possible delimiter
        self.preferred = [',', '\t', ';', ' ', ':']

def sniff(self, sample, delimiters=None):
        """
        Returns a dialect (or None) corresponding to the sample
        """

quotechar, doublequote, delimiter, skipinitialspace = \
                   self._guess_quote_and_delimiter(sample, delimiters)
        if not delimiter:
            delimiter, skipinitialspace = self._guess_delimiter(sample,
                                                                delimiters)

if not delimiter:
            raise Error("Could not determine delimiter")

class dialect(Dialect):
            _name = "sniffed"
            lineterminator = '\r\n'
            quoting = QUOTE_MINIMAL
            # escapechar = ''

dialect.doublequote = doublequote
        dialect.delimiter = delimiter
        # _csv.reader won't accept a quotechar of ''
        dialect.quotechar = quotechar or '"'
        dialect.skipinitialspace = skipinitialspace

return dialect

def _guess_quote_and_delimiter(self, data, delimiters):
        """
        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 (r'(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?P=delim)', # ,".*?",
                      r'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?P<delim>[^\w\n"\'])(?P<space> ?)',   #  ".*?",
                      r'(?P<delim>[^\w\n"\'])(?P<space> ?)(?P<quote>["\']).*?(?P=quote)(?:$|\n)',   # ,".*?"
                      r'(?:^|\n)(?P<quote>["\']).*?(?P=quote)(?:$|\n)'):                            #  ".*?" (no delim, no space)
            regexp = re.compile(restr, re.DOTALL | re.MULTILINE)
            matches = regexp.findall(data)
            if matches:
                break

if not matches:
            # (quotechar, doublequote, delimiter, skipinitialspace)
            return ('', False, None, 0)
        quotes = {}
        delims = {}
        spaces = 0
        groupindex = regexp.groupindex
        for m in matches:
            n = groupindex['quote'] - 1
            key = m[n]
            if key:
                quotes[key] = quotes.get(key, 0) + 1
            try:
                n = groupindex['delim'] - 1
                key = m[n]
            except KeyError:
                continue
            if key and (delimiters is None or key in delimiters):
                delims[key] = delims.get(key, 0) + 1
            try:
                n = groupindex['space'] - 1
            except KeyError:
                continue
            if m[n]:
                spaces += 1

quotechar = max(quotes, key=quotes.get)

if delims:
            delim = max(delims, key=delims.get)
            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

# if we see an extra quote between delimiters, we've got a
        # double quoted format
        dq_regexp = re.compile(
                               r"((%(delim)s)|^)\W*%(quote)s[^%(delim)s\n]*%(quote)s[^%(delim)s\n]*%(quote)s\W*((%(delim)s)|$)" % \
                               {'delim':re.escape(delim), 'quote':quotechar}, re.MULTILINE)

if dq_regexp.search(data):
            doublequote = True
        else:
            doublequote = False

return (quotechar, doublequote, delim, skipinitialspace)

def _guess_delimiter(self, data, delimiters):
        """
        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 frequencies 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 = list(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, chunkLength
        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.count(char)
                    # value is the mode
                    metaFrequency[freq] = metaFrequency.get(freq, 0) + 1
                    charFrequency[char] = metaFrequency

for char in charFrequency.keys():
                items = list(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] = max(items, key=lambda x: x[1])
                    # adjust the mode - subtract the sum of all
                    # other frequencies
                    items.remove(modes[char])
                    modes[char] = (modes[char][0], modes[char][1]
                                   - sum(item[1] for item in items))
                else:
                    modes[char] = items[0]

# build a list of possible delimiters
            modeList = modes.items()
            total = float(min(chunkLength * iteration, len(data)))
            # (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 and
                            (delimiters is None or k in delimiters)):
                            delims[k] = v
                consistency -= 0.01

if len(delims) == 1:
                delim = list(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)

# nothing else indicates a preference, pick the character that
        # dominates(?)
        items = [(v,k) for (k,v) in delims.items()]
        items.sort()
        delim = items[-1][1]

skipinitialspace = (data[0].count(delim) ==
                            data[0].count("%c " % delim))
        return (delim, 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()):

for thisType in [int, float, complex]:
                    try:
                        thisType(row[col])
                        break
                    except (ValueError, OverflowError):
                        pass
                else:
                    # 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:
                    colType(header[col])
                except (ValueError, TypeError):
                    hasHeader += 1
                else:
                    hasHeader -= 1

return hasHeader > 0

cmd: