Initial commit

app/utils/create_ngram_models.py

@@ -0,0 +1,36 @@
+"""
+Small script creating the models for the N-Gramm Viewer holding containing all
+the different n-gramm data.
+"""
+
+corpus_type_list = ["lm_ns_year", "tk_ws_year", "lm_ns_speaker", "tk_ws_speaker"]
+sort_key_list = ([i for i in range(10)]
+                 + "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()
+                 + ["_Non_ASCII"])
+ngram_kinds = ["One", "Two", "Three", "Four", "Five"]
+
+template_class = """
+class Key{}_{}Gram_{}(models.Model):
+    ngram = models.CharField(verbose_name='{}Gram',
+                             max_length=255,
+                             default=None,
+                             null=True,
+                             blank=True)
+    key = models.CharField(max_length=255)
+    count = models.IntegerField()
+
+    def __str__(self):
+        return str(self.ngram) + " " + str(self.key)
+                 """
+
+classes = []
+for corpus_type in corpus_type_list:
+    for ngram_kind in ngram_kinds:
+        for key in sort_key_list:
+            cls = template_class.format(key, ngram_kind, corpus_type,
+                                        ngram_kind)
+            classes.append(cls)
+
+with open("classes.txt", "w") as file:
+    for cls in classes:
+        file.write("{}\n".format(cls))