"""
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 collections import OrderedDict
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 = OrderedDict(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))
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, 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.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(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 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
I am a small town Minnesota single mom of two great kids who are my life. I began modeling 3 years ago for a photographer ho saw something in me I never did. Ice told me I should do one shoot with him and let that be the guide. I reluctantly agreed, and scheduled our date. I was sacred to death when he told me we would be doing a remake of the publicity stills of the 1956 movie Bus Stop, staring Marilyn Monroe. How in the world could I halfway resemble or pull off an icon the likes of Marylin Monroe in my first step in front of camera? Well, 2 hours later we had a nice set of images and I've been hooked ever since. We've done some really cool things and are looking hard at the future ahead to expand and get me out there a little more.
My pinup journey started at the age of 13 when I started collecting vintage decor and clothing- it has since spiraled into doing pinup shoots, meeting and developing friendships with other gorgeous pinups and being published in a pinup blog and magazine. Looking forward to the future and to see where other opportunities will take me!
Full Bio
I started getting into collecting vintage when I was a young kid, my mom would always take me into antique stores and this seemed to be what fueled it all. Eventually I started dressing and collecting vintage clothing and home decor. My apartment is now a great mix of MCM. I’ve done several pinup photoshoots and am looking to doing more in the future. I have been featured in a online pinup blog as well as being published in an state content creators magazine. Looking forward to the future and all the adventures it brings going forward.
Meet Belle Starr, your favorite tattooed 💉, curvy 💃 nurse turning heads and stealing hearts 💘 across Northwest Florida. A professional nurse 👩⚕️ during the week and a sultry pinup queen 👑 on the weekends, she’s the ultimate blend of classy ✨ and sassy 🔥—a vintage vixen with a modern twist.
Full Bio
Meet Belle Starr, your favorite tattooed 💉, curvy 💃 nurse turning heads and stealing hearts 💘 across Northwest Florida. A professional nurse 👩⚕️ during the week and a sultry pinup queen 👑 on the weekends, she’s the ultimate blend of classy ✨ and sassy 🔥—a vintage vixen with a modern twist.
She serves as the secretary for Pinups and Pumps Florida Chapter 💄 and is the official correspondent for PinupDatabase.com 🖋️. Belle Starr is dedicated to empowering women 👠, spotlighting the pinup community, and keeping the spirit of pinup history alive 📸. When she’s not hostessing 🎤 or interviewing at events 🌟, she’s a fierce advocate for the Ostel Place Foundation 🐴🐶🌿, a charity that helps people heal through horses, puppies, and the beauty of nature.
Whether she’s inspiring women 💋, enticing men 🕶️, or stealing the show as an event hostess 🎉, Belle Starr proves that beauty 💎, brains 🧠, and curves 🔥 never go out of style. Follow her journey for a dose of entertainment 🎭, empowerment 💪, and unforgettable vibes 🌟.
I'm a Pin Up model, classic car lover and Patriot. Been in Pin Up since 2014.
Full Bio
BoomBoom Bettie has been in the pinup world since 2014. She has participated in pageants in person and online since 2019. She loves the title of Favorite Pearl that she received. She is the founder of a Pin Up club called Black Sheep Pin Up Social Club in Arizona. She loves being a part of the pin up world and the sisterhood it creates. She loves to attend local car shows and Pin Up events.
𝑰 𝒑𝒐𝒔𝒕 my own pics, 𝒂𝒍𝒍 𝒄𝒍𝒂𝒔𝒔𝒚, 𝒖𝒔𝒖𝒂𝒍𝒍𝒚 𝒘𝒊𝒕𝒉 𝒇𝒖𝒏 𝒕𝒉𝒆𝒎𝒆𝒔. 𝑪𝒖𝒔𝒕𝒐𝒎 𝒘𝒐𝒓𝒌 𝒊𝒔 𝒂𝒗𝒂𝒊𝒍𝒂𝒃𝒍𝒆.
Jill of All, Owner of 5.
@currentteevents philanthropic tshirts
@shopcadesigns jewelry
@ciaraandruby dog models
@openmybar bar consulting
@calishamrock art/photography
My awesome journey began in California, followed by 25 wonderful years in Colorado. In 2019 I made the best choice of my life—moving to Florida, where I’ve truly found my home. The pin up community has been amazing, as I have always been drawn to the vibrant world of rockabilly style, classic cars, and music. Known for being kind, generous, and full of adventure, I cherish my experiences and connecting with new people. As a proud member of "Pinups and Pumps," I deeply appreciate the camaraderie with my sisters. Together, we give back through charity events, creating lasting bonds and memories.
Rating (average)
(0)
City
St. Augustine
Province
FL
Pin Up Group Membership
Pinups and Pumps Florida
Published in the Following Publications
Dream Beauty, Dream Pinup, Wonderland, Social Pin, Smitten Kitten, Dollface Digest, Crowns & Chrome, Drive In and many more
Clarice entered the pinup scene officially in 2019. Her first photoshoot was a tribute to the queen herself, Bettie Page. Dawning the same iconic bangs and hair darker than the devil's soul, she was a tattooed dead ringer. That photoshoot was featured in Retro Lovely's Bettie Page issue in 2019.
6 years later Clarice is a style of her own, finding herself more and more every day. She's a mental health advocate, constantly trying to educate about mental illness to help end the stigma. In March of this year she'll be celebrating 3 years free from alcohol. Supporting sobriety amongst her community is also a passion. Clarice is also Autistic, and tries to educate on hidden disabilities. Not only is she a pinup, she's a mommy first. Having 3 biological children, 3 "step"children, and her youngest being adopted, who's also autistic.
She enjoys creating art through painting, drawing, photography, and floral hair pieces.
Find her at the car shows, especially if there are rat rods and lowriders involved. Lowriders have been a part of her heart since high school. From being in a friend's hopper getting Taco Bell past her curfew, or cruising the beach with the systems bumping.
The name Clarice Von Darling is a tribute to The Silence of the Lambs. In her sister's memory.
62 year old trans woman who is now retired and living life to the fullest. Many past careers including dairy farmer firefighter/emt truck driver school bus driver church sexton cemetery sexton Public works director juice company truck driver and over the road truck driver. Two grown adult children ages 36 and 33 Two grand children ages 14 and 4 Local church member
