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Diffstat (limited to 'venv/Lib/site-packages/pip-19.0.3-py3.7.egg/pip/_vendor/chardet/hebrewprober.py')
| -rw-r--r-- | venv/Lib/site-packages/pip-19.0.3-py3.7.egg/pip/_vendor/chardet/hebrewprober.py | 292 |
1 files changed, 0 insertions, 292 deletions
diff --git a/venv/Lib/site-packages/pip-19.0.3-py3.7.egg/pip/_vendor/chardet/hebrewprober.py b/venv/Lib/site-packages/pip-19.0.3-py3.7.egg/pip/_vendor/chardet/hebrewprober.py deleted file mode 100644 index b0e1bf4..0000000 --- a/venv/Lib/site-packages/pip-19.0.3-py3.7.egg/pip/_vendor/chardet/hebrewprober.py +++ /dev/null @@ -1,292 +0,0 @@ -######################## BEGIN LICENSE BLOCK ######################## -# The Original Code is Mozilla Universal charset detector code. -# -# The Initial Developer of the Original Code is -# Shy Shalom -# Portions created by the Initial Developer are Copyright (C) 2005 -# the Initial Developer. All Rights Reserved. -# -# Contributor(s): -# Mark Pilgrim - port to Python -# -# 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 ProbingState - -# This prober doesn't actually recognize a language or a charset. -# It is a helper prober for the use of the Hebrew model probers - -### General ideas of the Hebrew charset recognition ### -# -# Four main charsets exist in Hebrew: -# "ISO-8859-8" - Visual Hebrew -# "windows-1255" - Logical Hebrew -# "ISO-8859-8-I" - Logical Hebrew -# "x-mac-hebrew" - ?? Logical Hebrew ?? -# -# Both "ISO" charsets use a completely identical set of code points, whereas -# "windows-1255" and "x-mac-hebrew" are two different proper supersets of -# these code points. windows-1255 defines additional characters in the range -# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific -# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6. -# x-mac-hebrew defines similar additional code points but with a different -# mapping. -# -# As far as an average Hebrew text with no diacritics is concerned, all four -# charsets are identical with respect to code points. Meaning that for the -# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters -# (including final letters). -# -# The dominant difference between these charsets is their directionality. -# "Visual" directionality means that the text is ordered as if the renderer is -# not aware of a BIDI rendering algorithm. The renderer sees the text and -# draws it from left to right. The text itself when ordered naturally is read -# backwards. A buffer of Visual Hebrew generally looks like so: -# "[last word of first line spelled backwards] [whole line ordered backwards -# and spelled backwards] [first word of first line spelled backwards] -# [end of line] [last word of second line] ... etc' " -# adding punctuation marks, numbers and English text to visual text is -# naturally also "visual" and from left to right. -# -# "Logical" directionality means the text is ordered "naturally" according to -# the order it is read. It is the responsibility of the renderer to display -# the text from right to left. A BIDI algorithm is used to place general -# punctuation marks, numbers and English text in the text. -# -# Texts in x-mac-hebrew are almost impossible to find on the Internet. From -# what little evidence I could find, it seems that its general directionality -# is Logical. -# -# To sum up all of the above, the Hebrew probing mechanism knows about two -# charsets: -# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are -# backwards while line order is natural. For charset recognition purposes -# the line order is unimportant (In fact, for this implementation, even -# word order is unimportant). -# Logical Hebrew - "windows-1255" - normal, naturally ordered text. -# -# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be -# specifically identified. -# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew -# that contain special punctuation marks or diacritics is displayed with -# some unconverted characters showing as question marks. This problem might -# be corrected using another model prober for x-mac-hebrew. Due to the fact -# that x-mac-hebrew texts are so rare, writing another model prober isn't -# worth the effort and performance hit. -# -#### The Prober #### -# -# The prober is divided between two SBCharSetProbers and a HebrewProber, -# all of which are managed, created, fed data, inquired and deleted by the -# SBCSGroupProber. The two SBCharSetProbers identify that the text is in -# fact some kind of Hebrew, Logical or Visual. The final decision about which -# one is it is made by the HebrewProber by combining final-letter scores -# with the scores of the two SBCharSetProbers to produce a final answer. -# -# The SBCSGroupProber is responsible for stripping the original text of HTML -# tags, English characters, numbers, low-ASCII punctuation characters, spaces -# and new lines. It reduces any sequence of such characters to a single space. -# The buffer fed to each prober in the SBCS group prober is pure text in -# high-ASCII. -# The two SBCharSetProbers (model probers) share the same language model: -# Win1255Model. -# The first SBCharSetProber uses the model normally as any other -# SBCharSetProber does, to recognize windows-1255, upon which this model was -# built. The second SBCharSetProber is told to make the pair-of-letter -# lookup in the language model backwards. This in practice exactly simulates -# a visual Hebrew model using the windows-1255 logical Hebrew model. -# -# The HebrewProber is not using any language model. All it does is look for -# final-letter evidence suggesting the text is either logical Hebrew or visual -# Hebrew. Disjointed from the model probers, the results of the HebrewProber -# alone are meaningless. HebrewProber always returns 0.00 as confidence -# since it never identifies a charset by itself. Instead, the pointer to the -# HebrewProber is passed to the model probers as a helper "Name Prober". -# When the Group prober receives a positive identification from any prober, -# it asks for the name of the charset identified. If the prober queried is a -# Hebrew model prober, the model prober forwards the call to the -# HebrewProber to make the final decision. In the HebrewProber, the -# decision is made according to the final-letters scores maintained and Both -# model probers scores. The answer is returned in the form of the name of the -# charset identified, either "windows-1255" or "ISO-8859-8". - -class HebrewProber(CharSetProber): - # windows-1255 / ISO-8859-8 code points of interest - FINAL_KAF = 0xea - NORMAL_KAF = 0xeb - FINAL_MEM = 0xed - NORMAL_MEM = 0xee - FINAL_NUN = 0xef - NORMAL_NUN = 0xf0 - FINAL_PE = 0xf3 - NORMAL_PE = 0xf4 - FINAL_TSADI = 0xf5 - NORMAL_TSADI = 0xf6 - - # Minimum Visual vs Logical final letter score difference. - # If the difference is below this, don't rely solely on the final letter score - # distance. - MIN_FINAL_CHAR_DISTANCE = 5 - - # Minimum Visual vs Logical model score difference. - # If the difference is below this, don't rely at all on the model score - # distance. - MIN_MODEL_DISTANCE = 0.01 - - VISUAL_HEBREW_NAME = "ISO-8859-8" - LOGICAL_HEBREW_NAME = "windows-1255" - - def __init__(self): - super(HebrewProber, self).__init__() - self._final_char_logical_score = None - self._final_char_visual_score = None - self._prev = None - self._before_prev = None - self._logical_prober = None - self._visual_prober = None - self.reset() - - def reset(self): - self._final_char_logical_score = 0 - self._final_char_visual_score = 0 - # The two last characters seen in the previous buffer, - # mPrev and mBeforePrev are initialized to space in order to simulate - # a word delimiter at the beginning of the data - self._prev = ' ' - self._before_prev = ' ' - # These probers are owned by the group prober. - - def set_model_probers(self, logicalProber, visualProber): - self._logical_prober = logicalProber - self._visual_prober = visualProber - - def is_final(self, c): - return c in [self.FINAL_KAF, self.FINAL_MEM, self.FINAL_NUN, - self.FINAL_PE, self.FINAL_TSADI] - - def is_non_final(self, c): - # The normal Tsadi is not a good Non-Final letter due to words like - # 'lechotet' (to chat) containing an apostrophe after the tsadi. This - # apostrophe is converted to a space in FilterWithoutEnglishLetters - # causing the Non-Final tsadi to appear at an end of a word even - # though this is not the case in the original text. - # The letters Pe and Kaf rarely display a related behavior of not being - # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak' - # for example legally end with a Non-Final Pe or Kaf. However, the - # benefit of these letters as Non-Final letters outweighs the damage - # since these words are quite rare. - return c in [self.NORMAL_KAF, self.NORMAL_MEM, - self.NORMAL_NUN, self.NORMAL_PE] - - def feed(self, byte_str): - # Final letter analysis for logical-visual decision. - # Look for evidence that the received buffer is either logical Hebrew - # or visual Hebrew. - # The following cases are checked: - # 1) A word longer than 1 letter, ending with a final letter. This is - # an indication that the text is laid out "naturally" since the - # final letter really appears at the end. +1 for logical score. - # 2) A word longer than 1 letter, ending with a Non-Final letter. In - # normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi, - # should not end with the Non-Final form of that letter. Exceptions - # to this rule are mentioned above in isNonFinal(). This is an - # indication that the text is laid out backwards. +1 for visual - # score - # 3) A word longer than 1 letter, starting with a final letter. Final - # letters should not appear at the beginning of a word. This is an - # indication that the text is laid out backwards. +1 for visual - # score. - # - # The visual score and logical score are accumulated throughout the - # text and are finally checked against each other in GetCharSetName(). - # No checking for final letters in the middle of words is done since - # that case is not an indication for either Logical or Visual text. - # - # We automatically filter out all 7-bit characters (replace them with - # spaces) so the word boundary detection works properly. [MAP] - - if self.state == ProbingState.NOT_ME: - # Both model probers say it's not them. No reason to continue. - return ProbingState.NOT_ME - - byte_str = self.filter_high_byte_only(byte_str) - - for cur in byte_str: - if cur == ' ': - # We stand on a space - a word just ended - if self._before_prev != ' ': - # next-to-last char was not a space so self._prev is not a - # 1 letter word - if self.is_final(self._prev): - # case (1) [-2:not space][-1:final letter][cur:space] - self._final_char_logical_score += 1 - elif self.is_non_final(self._prev): - # case (2) [-2:not space][-1:Non-Final letter][ - # cur:space] - self._final_char_visual_score += 1 - else: - # Not standing on a space - if ((self._before_prev == ' ') and - (self.is_final(self._prev)) and (cur != ' ')): - # case (3) [-2:space][-1:final letter][cur:not space] - self._final_char_visual_score += 1 - self._before_prev = self._prev - self._prev = cur - - # Forever detecting, till the end or until both model probers return - # ProbingState.NOT_ME (handled above) - return ProbingState.DETECTING - - @property - def charset_name(self): - # Make the decision: is it Logical or Visual? - # If the final letter score distance is dominant enough, rely on it. - finalsub = self._final_char_logical_score - self._final_char_visual_score - if finalsub >= self.MIN_FINAL_CHAR_DISTANCE: - return self.LOGICAL_HEBREW_NAME - if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE: - return self.VISUAL_HEBREW_NAME - - # It's not dominant enough, try to rely on the model scores instead. - modelsub = (self._logical_prober.get_confidence() - - self._visual_prober.get_confidence()) - if modelsub > self.MIN_MODEL_DISTANCE: - return self.LOGICAL_HEBREW_NAME - if modelsub < -self.MIN_MODEL_DISTANCE: - return self.VISUAL_HEBREW_NAME - - # Still no good, back to final letter distance, maybe it'll save the - # day. - if finalsub < 0.0: - return self.VISUAL_HEBREW_NAME - - # (finalsub > 0 - Logical) or (don't know what to do) default to - # Logical. - return self.LOGICAL_HEBREW_NAME - - @property - def language(self): - return 'Hebrew' - - @property - def state(self): - # Remain active as long as any of the model probers are active. - if (self._logical_prober.state == ProbingState.NOT_ME) and \ - (self._visual_prober.state == ProbingState.NOT_ME): - return ProbingState.NOT_ME - return ProbingState.DETECTING |