--- a/env/lib/python3.7/site-packages/chardet/sbcharsetprober.py	Thu May 14 16:47:39 2020 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,132 +0,0 @@
-######################## BEGIN LICENSE BLOCK ########################
-# The Original Code is Mozilla Universal charset detector code.
-#
-# The Initial Developer of the Original Code is
-# Netscape Communications Corporation.
-# Portions created by the Initial Developer are Copyright (C) 2001
-# the Initial Developer. All Rights Reserved.
-#
-# Contributor(s):
-#   Mark Pilgrim - port to Python
-#   Shy Shalom - original C code
-#
-# This library is free software; you can redistribute it and/or
-# modify it under the terms of the GNU Lesser General Public
-# License as published by the Free Software Foundation; either
-# version 2.1 of the License, or (at your option) any later version.
-#
-# This library is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-# Lesser General Public License for more details.
-#
-# You should have received a copy of the GNU Lesser General Public
-# License along with this library; if not, write to the Free Software
-# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
-# 02110-1301  USA
-######################### END LICENSE BLOCK #########################
-
-from .charsetprober import CharSetProber
-from .enums import CharacterCategory, ProbingState, SequenceLikelihood
-
-
-class SingleByteCharSetProber(CharSetProber):
-    SAMPLE_SIZE = 64
-    SB_ENOUGH_REL_THRESHOLD = 1024  #  0.25 * SAMPLE_SIZE^2
-    POSITIVE_SHORTCUT_THRESHOLD = 0.95
-    NEGATIVE_SHORTCUT_THRESHOLD = 0.05
-
-    def __init__(self, model, reversed=False, name_prober=None):
-        super(SingleByteCharSetProber, self).__init__()
-        self._model = model
-        # TRUE if we need to reverse every pair in the model lookup
-        self._reversed = reversed
-        # Optional auxiliary prober for name decision
-        self._name_prober = name_prober
-        self._last_order = None
-        self._seq_counters = None
-        self._total_seqs = None
-        self._total_char = None
-        self._freq_char = None
-        self.reset()
-
-    def reset(self):
-        super(SingleByteCharSetProber, self).reset()
-        # char order of last character
-        self._last_order = 255
-        self._seq_counters = [0] * SequenceLikelihood.get_num_categories()
-        self._total_seqs = 0
-        self._total_char = 0
-        # characters that fall in our sampling range
-        self._freq_char = 0
-
-    @property
-    def charset_name(self):
-        if self._name_prober:
-            return self._name_prober.charset_name
-        else:
-            return self._model['charset_name']
-
-    @property
-    def language(self):
-        if self._name_prober:
-            return self._name_prober.language
-        else:
-            return self._model.get('language')
-
-    def feed(self, byte_str):
-        if not self._model['keep_english_letter']:
-            byte_str = self.filter_international_words(byte_str)
-        if not byte_str:
-            return self.state
-        char_to_order_map = self._model['char_to_order_map']
-        for i, c in enumerate(byte_str):
-            # XXX: Order is in range 1-64, so one would think we want 0-63 here,
-            #      but that leads to 27 more test failures than before.
-            order = char_to_order_map[c]
-            # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but
-            #      CharacterCategory.SYMBOL is actually 253, so we use CONTROL
-            #      to make it closer to the original intent. The only difference
-            #      is whether or not we count digits and control characters for
-            #      _total_char purposes.
-            if order < CharacterCategory.CONTROL:
-                self._total_char += 1
-            if order < self.SAMPLE_SIZE:
-                self._freq_char += 1
-                if self._last_order < self.SAMPLE_SIZE:
-                    self._total_seqs += 1
-                    if not self._reversed:
-                        i = (self._last_order * self.SAMPLE_SIZE) + order
-                        model = self._model['precedence_matrix'][i]
-                    else:  # reverse the order of the letters in the lookup
-                        i = (order * self.SAMPLE_SIZE) + self._last_order
-                        model = self._model['precedence_matrix'][i]
-                    self._seq_counters[model] += 1
-            self._last_order = order
-
-        charset_name = self._model['charset_name']
-        if self.state == ProbingState.DETECTING:
-            if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD:
-                confidence = self.get_confidence()
-                if confidence > self.POSITIVE_SHORTCUT_THRESHOLD:
-                    self.logger.debug('%s confidence = %s, we have a winner',
-                                      charset_name, confidence)
-                    self._state = ProbingState.FOUND_IT
-                elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD:
-                    self.logger.debug('%s confidence = %s, below negative '
-                                      'shortcut threshhold %s', charset_name,
-                                      confidence,
-                                      self.NEGATIVE_SHORTCUT_THRESHOLD)
-                    self._state = ProbingState.NOT_ME
-
-        return self.state
-
-    def get_confidence(self):
-        r = 0.01
-        if self._total_seqs > 0:
-            r = ((1.0 * self._seq_counters[SequenceLikelihood.POSITIVE]) /
-                 self._total_seqs / self._model['typical_positive_ratio'])
-            r = r * self._freq_char / self._total_char
-            if r >= 1.0:
-                r = 0.99
-        return r