2019-02-28 13:09:53 +00:00
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"""
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2019-03-01 19:55:41 +00:00
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Small script creating the models for the N-Gramm Viewer containing all
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2019-02-28 13:09:53 +00:00
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the different n-gramm data.
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"""
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corpus_type_list = ["lm_ns_year", "tk_ws_year", "lm_ns_speaker", "tk_ws_speaker"]
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sort_key_list = ([i for i in range(10)]
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+ "A B C D E F G H I J K L M N O P Q R S T U V W X Y Z".split()
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+ ["_Non_ASCII"])
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ngram_kinds = ["One", "Two", "Three", "Four", "Five"]
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template_class = """
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class Key{}_{}Gram_{}(models.Model):
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ngram = models.CharField(verbose_name='{}Gram',
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max_length=255,
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default=None,
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null=True,
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blank=True)
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key = models.CharField(max_length=255)
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count = models.IntegerField()
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def __str__(self):
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return str(self.ngram) + " " + str(self.key)
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"""
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classes = []
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for corpus_type in corpus_type_list:
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for ngram_kind in ngram_kinds:
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for key in sort_key_list:
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cls = template_class.format(key, ngram_kind, corpus_type,
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ngram_kind)
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classes.append(cls)
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with open("classes.txt", "w") as file:
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for cls in classes:
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file.write("{}\n".format(cls))
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