diff venv/lib/python2.7/site-packages/requests/packages/chardet/hebrewprober.py @ 0:d67268158946 draft

planemo upload commit a3f181f5f126803c654b3a66dd4e83a48f7e203b

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/venv/lib/python2.7/site-packages/requests/packages/chardet/hebrewprober.py	Mon Oct 12 17:43:33 2015 -0400
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+######################## 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 .constants import eNotMe, eDetecting
+from .compat import wrap_ord
+
+# 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".
+
+# 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"
+
+
+class HebrewProber(CharSetProber):
+    def __init__(self):
+        CharSetProber.__init__(self)
+        self._mLogicalProber = None
+        self._mVisualProber = None
+        self.reset()
+
+    def reset(self):
+        self._mFinalCharLogicalScore = 0
+        self._mFinalCharVisualScore = 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._mPrev = ' '
+        self._mBeforePrev = ' '
+        # These probers are owned by the group prober.
+
+    def set_model_probers(self, logicalProber, visualProber):
+        self._mLogicalProber = logicalProber
+        self._mVisualProber = visualProber
+
+    def is_final(self, c):
+        return wrap_ord(c) in [FINAL_KAF, FINAL_MEM, FINAL_NUN, FINAL_PE,
+                               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 wrap_ord(c) in [NORMAL_KAF, NORMAL_MEM, NORMAL_NUN, NORMAL_PE]
+
+    def feed(self, aBuf):
+        # 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.get_state() == eNotMe:
+            # Both model probers say it's not them. No reason to continue.
+            return eNotMe
+
+        aBuf = self.filter_high_bit_only(aBuf)
+
+        for cur in aBuf:
+            if cur == ' ':
+                # We stand on a space - a word just ended
+                if self._mBeforePrev != ' ':
+                    # next-to-last char was not a space so self._mPrev is not a
+                    # 1 letter word
+                    if self.is_final(self._mPrev):
+                        # case (1) [-2:not space][-1:final letter][cur:space]
+                        self._mFinalCharLogicalScore += 1
+                    elif self.is_non_final(self._mPrev):
+                        # case (2) [-2:not space][-1:Non-Final letter][
+                        #  cur:space]
+                        self._mFinalCharVisualScore += 1
+            else:
+                # Not standing on a space
+                if ((self._mBeforePrev == ' ') and
+                        (self.is_final(self._mPrev)) and (cur != ' ')):
+                    # case (3) [-2:space][-1:final letter][cur:not space]
+                    self._mFinalCharVisualScore += 1
+            self._mBeforePrev = self._mPrev
+            self._mPrev = cur
+
+        # Forever detecting, till the end or until both model probers return
+        # eNotMe (handled above)
+        return eDetecting
+
+    def get_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._mFinalCharLogicalScore - self._mFinalCharVisualScore
+        if finalsub >= MIN_FINAL_CHAR_DISTANCE:
+            return LOGICAL_HEBREW_NAME
+        if finalsub <= -MIN_FINAL_CHAR_DISTANCE:
+            return VISUAL_HEBREW_NAME
+
+        # It's not dominant enough, try to rely on the model scores instead.
+        modelsub = (self._mLogicalProber.get_confidence()
+                    - self._mVisualProber.get_confidence())
+        if modelsub > MIN_MODEL_DISTANCE:
+            return LOGICAL_HEBREW_NAME
+        if modelsub < -MIN_MODEL_DISTANCE:
+            return VISUAL_HEBREW_NAME
+
+        # Still no good, back to final letter distance, maybe it'll save the
+        # day.
+        if finalsub < 0.0:
+            return VISUAL_HEBREW_NAME
+
+        # (finalsub > 0 - Logical) or (don't know what to do) default to
+        # Logical.
+        return LOGICAL_HEBREW_NAME
+
+    def get_state(self):
+        # Remain active as long as any of the model probers are active.
+        if (self._mLogicalProber.get_state() == eNotMe) and \
+           (self._mVisualProber.get_state() == eNotMe):
+            return eNotMe
+        return eDetecting