forgot to set up a git repo, so here it is
This commit is contained in:
Phuntsok Drak-pa
commit
1245552e24
1
.gitignore
esterno
Normal file
1
.gitignore
esterno
Normal file
@ -0,0 +1 @@
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*.xml
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1022663
dico.dictfr
Normal file
1022663
dico.dictfr
Normal file
File diff soppresso perché troppo grande
Carica Diff
14247
les_miserables_tomeI.txt
Normal file
14247
les_miserables_tomeI.txt
Normal file
File diff soppresso perché troppo grande
Carica Diff
475
parser.py
Executable file
475
parser.py
Executable file
@ -0,0 +1,475 @@
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#!/usr/bin/env python3
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###############################################################################
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# imports #
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###############################################################################
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import csv
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import re
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import sys
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import xml.etree.cElementTree as ET
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###############################################################################
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# Regex #
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###############################################################################
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# Sometimes some words are splitted, this regex re-merge them.
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blanks_between_points = re.compile('(?<=[\!\?\.]) (?=[\!\?\.])')
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# This regex will find groups of ending punctuation (!, ? or .)
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# It will be used to splt text in sentences
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ending_punctuation = re.compile('[\!\?\.]+')
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# This regex checks that end of argument given to this program contains at
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# least one alphanumeric character followed by ".txt" characters. It is use
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# twice:
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# - Argument conformity verification
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# - Resulting file creation
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# ("txt" characters of argument are replaced by "xml")
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filename_end = re.compile('(?<=\w\.)txt$')
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# This regex is used to replace -, ", ', ;, : & , characters (eventually
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# grouped) by a single space
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intermediate_punctuation = re.compile('[\,\;\:\"\'\-]+')
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# Goal of this regex is to replace groups of whites characters
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# (\n, \r, \t, \s) by single spaces
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whites = re.compile('[\n\r\t ]+')
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# Sometimes some words are splitted, this regex re-merge them
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word_breaks = re.compile('\-[\n\r]+')
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###############################################################################
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# global variables #
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###############################################################################
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french_chars = "abcdefghijklmnopqrstuvwxyzàâæÇçéèêëîïôœùûüÿ"
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# input text to parse
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txt = ""
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# dictionary of words loaded from linguistic dictionary
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dictionary = {}
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wordtype = {
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'N': "noun",
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'V': "verb",
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'P': "pronoun",
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'A': "adjective",
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'D': "determiner",
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'R': "adverb",
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'S': "adposition",
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'C': "conjonction",
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'I': "interjection",
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'X': "residual",
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'F': "ponctuation",
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'?': "unknown"
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}
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nountypes = {'c': "common", 'p': "proper", 'k': "cardinal", '-': "None"}
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verbtypes = {'m': "main", 'a': "auxiliary", '-': "None"}
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verbmood = {
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'i': "indicative",
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's': "subjunctive",
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'm': "imperative",
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'c': "conditional",
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'n': "infinitive",
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'p': "participle",
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'-': "None"
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}
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verbtense = {
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'p': "present",
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'i': "imperfect",
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'f': "future",
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's': "past",
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'-': "None"
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}
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adjtype = {
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'f': "qualifiative",
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'o': "ordinal",
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'k': "cardinal",
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'i': "indefinite",
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's': "possessive",
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'-': "None"
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}
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degree = {'p': "positive", 'c': "comparative", 'n': "negative", '-': "None"}
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pronountype = {
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'p': "personal",
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'd': "demanstrative",
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'i': "indefinite",
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's': "possessive",
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't': "interrogative",
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'r': "relative",
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'x': "reflexive",
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'k': "cardinal",
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'-': "None"
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}
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pronouncase = {
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'n': "nominative",
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'a': "accusative",
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'd': "dative",
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'o': "oblique",
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'g': "genitive",
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'-': "None"
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}
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detertypes = {
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'a': "article",
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'd': "demonstrative",
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's': "possessive",
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'i': "indefinite",
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't': "iter-excl",
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'r': "relative",
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'k': "cardinal",
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'-': "None"
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}
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deternature = {'d': "definite", 'i': "indefinite", '-': "None"}
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advtypes = {'g': "general", 'p': "particle", 'x': "interro-excl", '-': "None"}
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adptypes = {'p': "preposition", 'd': "deictique", '-': "None"}
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conjtypes = {'c': "coordinative", 's': "subortinative", '-': "None"}
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gender = {'m': "masculine", 'f': "feminine", '-': "None"}
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number = {'s': "singular", 'p': "plural", '-': "None"}
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person = {'1': "first", '2': "second", '3': "third", '-': "None"}
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###############################################################################
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# classes definition #
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###############################################################################
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class Word:
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"""Any word found in the language's dictionary. It contains its plain
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string representation, an array of GRACE descriptions, an array of its word
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categories, its phonetics and its frequency in the working text.
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"""
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def __init__(self, word: str, grammar, phonetics: str):
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"""Constructor of the `Word` class. It accepts as arguments a string
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(its plain string representation), an array of strings (GRACE
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description of the word) and its phonetics as string too.
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"""
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self.__word = word
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self.__grace = grammar
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self.__category = []
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for x in grammar:
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self.__category.append(x[0])
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self.__phon = phonetics
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self.__frequency = 0
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def __str__(self):
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"""Returns stringified `Word`"""
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res = self.__word + "\t/" + self.__phon + "/"
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for elem in self.__grace:
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res += "\n\t" + graceToDebugString(elem)
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return res
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def get_word(self):
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"""Returns plain string representation of `Word`"""
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return self.__word[:]
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def get_grace(self):
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"""Returns array of GRACE descriptions (string) of `Word`"""
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return self.__grace[:]
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def get_phon(self):
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"""Returns phonetics of `Word` as string"""
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return self.__phon[:]
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def increase_frequency(self):
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"""Increace by one the frequency of `Word`"""
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self.__frequency += 1
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def get_frequency(self):
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"""Get frequency of `Word` as number"""
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return self.__frequency
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###############################################################################
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# functions definition #
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###############################################################################
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def graceToDebugString(grace: str):
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"""Turns into a single string a GRACE description
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For debug purposes only
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"""
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res = wordtype[grace[0]]
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if grace[0] == 'N':
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# pass
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res += " " + nountypes[grace[1]]
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res += " " + gender[grace[2]]
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res += " " + number[grace[3]]
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elif grace[0] == 'V':
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res += " " + verbtypes[grace[1]]
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res += " " + verbmood[grace[2]]
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res += " " + verbtense[grace[3]]
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res += " " + person[grace[4]]
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res += " " + number[grace[5]]
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res += " " + gender[grace[6]]
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elif grace[0] == 'P':
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res += " " + pronountype[grace[1]]
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res += " " + person[grace[2]]
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res += " " + gender[grace[3]]
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res += " " + number[grace[4]]
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res += " " + pronouncase[grace[5]]
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res += " " + number[grace[6]]
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elif grace[0] == 'A':
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res += " " + adjtype[grace[1]]
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res += " " + degree[grace[2]]
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res += " " + gender[grace[3]]
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res += " " + number[grace[4]]
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elif grace[0] == 'D':
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res += " " + detertypes[grace[1]]
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res += " " + person[grace[2]]
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res += " " + gender[grace[3]]
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res += " " + number[grace[4]]
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res += " " + number[grace[5]]
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res += " " + deternature[grace[6]]
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elif grace[0] == 'R':
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res += " " + advtypes[grace[1]]
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res += " " + degree[grace[2]]
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elif grace[0] == 'S':
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res += " " + adptypes[grace[1]]
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elif grace[0] == 'C':
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res += " " + conjtypes[grace[1]]
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elif grace[0] == 'I':
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pass
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elif grace[0] == 'X':
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pass
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elif grace[0] == 'F':
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pass
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elif grace[0] == '?':
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pass
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return res
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def graceToString(grace: str):
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"""Returns an array of strings of explicit GRACE description"""
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if grace[0] == 'N':
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return [
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wordtype[grace[0]], nountypes[grace[1]], gender[grace[2]],
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number[grace[3]]
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]
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if grace[0] == 'V':
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return [
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wordtype[grace[0]], verbtypes[grace[1]], verbmood[grace[2]],
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verbtense[grace[3]], person[grace[4]], number[grace[5]],
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gender[grace[6]]
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]
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if grace[0] == 'P':
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return [
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wordtype[grace[0]], pronountype[grace[1]], person[grace[2]],
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gender[grace[3]], number[grace[4]], pronouncase[grace[5]],
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number[grace[6]]
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]
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if grace[0] == 'A':
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return [
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wordtype[grace[0]], adjtype[grace[1]], degree[grace[2]],
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gender[grace[3]], number[grace[4]]
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]
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if grace[0] == 'D':
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return [
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wordtype[grace[0]], detertypes[grace[1]], person[grace[2]],
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gender[grace[3]], number[grace[4]], number[grace[5]],
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deternature[grace[6]]
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]
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if grace[0] == 'R':
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return [wordtype[grace[0]], advtypes[grace[1]], degree[grace[2]]]
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if grace[0] == 'S':
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return [wordtype[grace[0]], adptypes[grace[1]]]
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if grace[0] == 'C':
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return [wordtype[grace[0]], conjtypes[grace[1]]]
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return [wordtype[grace[0]]]
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def init_dictionary():
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"""Loads the language's dictionary, its format being a comma-separated CSV,
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in its first collumn the word itself, in the second semicolon-separated
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GRACE definition of the word, and in the third collumn the word’s X-SAMPA
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phonetics
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"""
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with open('dico.dictfr', newline='') as csvfile:
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spamreader = csv.reader(csvfile, delimiter=',', quotechar='"')
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for row in spamreader:
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grammar = row[1]
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if grammar.find(';') != -1:
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grammar = grammar.split(';')
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else:
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grammar = [grammar]
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dictionary[row[0]] = Word(row[0], grammar, row[2])
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def clean_txt(txt):
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"""This function cleans string given as argument"""
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# Sometimes some words are splitted, this regex re-merge them
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txt = word_breaks.sub('', txt)
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# All of :;,'"- characters will be replaced by a space
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txt = intermediate_punctuation.sub(' ', txt)
|
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|
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# All whites characters groups (\n, \r, \t & \s) will be replaced by a
|
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# single space
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txt = whites.sub(' ', txt)
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# All whites characters between ending points (!, ? or .) will be removed
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txt = blanks_between_points.sub('', txt)
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return txt
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def filter_text(txt):
|
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"""This function constructs a list of filtered sentences. Each filtered
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sentence is itself a list of strings. Each string is a word found in the
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dictionary. In the same time a dict is built, containing selected words as
|
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keys and their frequencies as values."""
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filtered_text = []
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for sentence in filter(None, ending_punctuation.split(clean_txt(txt))):
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word_list = []
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for word in filter(None, sentence.split()):
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lower_word = word.lower()
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if lower_word not in dictionary:
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dictionary[lower_word] = Word(lower_word, ["?"], "")
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word_list.append(lower_word)
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dictionary[lower_word].increase_frequency()
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if word_list != []:
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filtered_text.append(word_list)
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return filtered_text
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def prepare_output(splitted_txt):
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text = ET.Element("text")
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for elem_sentence in splitted_txt:
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sentence = ET.SubElement(text, "sentence")
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for elem_word in elem_sentence:
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word = dictionary[elem_word]
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# First GRACE description used
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grace = word.get_grace()[0]
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grace_details = graceToString(grace)
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try:
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if grace[0] == 'N':
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ET.SubElement(
|
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sentence,
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"word",
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frequency=str(word.get_frequency()),
|
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wordclass=grace_details[0],
|
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wordtype=grace_details[1],
|
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gender=grace_details[2],
|
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number=grace_details[3]).text = word.get_word()
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elif grace[0] == 'V':
|
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ET.SubElement(
|
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sentence,
|
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"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=grace_details[0],
|
||||
wordtype=grace_details[1],
|
||||
mood=grace_details[2],
|
||||
tense=grace_details[3],
|
||||
person=grace_details[4],
|
||||
number=grace_details[5],
|
||||
gender=grace_details[6]).text = word.get_word()
|
||||
elif grace[0] == 'P':
|
||||
ET.SubElement(
|
||||
sentence,
|
||||
"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=grace_details[0],
|
||||
wordtype=grace_details[1],
|
||||
person=grace_details[2],
|
||||
gender=grace_details[3],
|
||||
number=grace_details[4],
|
||||
case=grace_details[5],
|
||||
possessor=grace_details[6]).text = word.get_word()
|
||||
elif grace[0] == 'A':
|
||||
ET.SubElement(
|
||||
sentence,
|
||||
"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=grace_details[0],
|
||||
wordtype=grace_details[1],
|
||||
degree=grace_details[2],
|
||||
gender=grace_details[3],
|
||||
number=grace_details[4]).text = word.get_word()
|
||||
elif grace[0] == 'D':
|
||||
ET.SubElement(
|
||||
sentence,
|
||||
"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=grace_details[0],
|
||||
wordtype=grace_details[1],
|
||||
person=grace_details[2],
|
||||
gender=grace_details[3],
|
||||
number=grace_details[4],
|
||||
possessor=grace_details[5],
|
||||
nature=grace_details[6]).text = word.get_word()
|
||||
elif grace[0] == 'R':
|
||||
ET.SubElement(
|
||||
sentence,
|
||||
"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=grace_details[0],
|
||||
wordtype=grace_details[1],
|
||||
degree=grace_details[2]).text = word.get_word()
|
||||
elif grace[0] == 'S' or grace[0] == 'C':
|
||||
ET.SubElement(
|
||||
sentence,
|
||||
"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=grace_details[0],
|
||||
wordtype=grace_details[1]).text = word.get_word()
|
||||
else:
|
||||
ET.SubElement(
|
||||
sentence,
|
||||
"word",
|
||||
frequency=str(word.get_frequency()),
|
||||
wordclass=str(
|
||||
grace_details[0])).text = word.get_word()
|
||||
except IndexError:
|
||||
print("Failed on " + word.get_word() + "\tGRACE:" + grace)
|
||||
return text
|
||||
|
||||
|
||||
###############################################################################
|
||||
# main program #
|
||||
###############################################################################
|
||||
|
||||
if __name__ == "__main__":
|
||||
# arg parse ###################################################################
|
||||
if len(sys.argv) < 2 or filename_end.findall(sys.argv[1]) == []:
|
||||
exit("Usage: ./parser.py *.txt")
|
||||
|
||||
# load files ##################################################################
|
||||
print("Loading input file...", end='')
|
||||
with open(sys.argv[1], 'r') as txt_file:
|
||||
txt = txt_file.read()
|
||||
print("\rInput file loaded ")
|
||||
print("Loading dictionary...", end='')
|
||||
init_dictionary()
|
||||
print("\r" + str(len(dictionary)) + " words loaded")
|
||||
|
||||
# now comes the parsing work ##################################################
|
||||
|
||||
filtered_text = filter_text(txt)
|
||||
root = prepare_output(filtered_text)
|
||||
tree = ET.ElementTree(root)
|
||||
tree.write(
|
||||
filename_end.sub('xml', sys.argv[1]),
|
||||
xml_declaration=True,
|
||||
encoding='utf-8',
|
||||
method="xml")
|
||||
exit(0)
|
||||
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