Remove visualization app (#47)

* remove unused files and code

* remove requests from pipfile

* remove required from author in profile

* change create() to update_or_create() if profile has the same id_in_channel and channel

Pipfile

@@ -14,15 +14,6 @@ djangorestframework = "==3.7.7"
 django-filter = "*"
 django-nested-admin = "*"
 gunicorn = "*"
-django-compressor = "*"
-django-compressor-toolkit = "*"
-django-npm = "*"
-nltk = "*"
-jupyter = "*"
-requests = "*"
-pprint = "*"
-jsonfield = "*"
-click = "*"
 
 [requires]
 python_version = "3.6"

src/apps/core/models.py

@@ -138,7 +138,11 @@ class Meta:
         verbose_name_plural = _('profiles')
 
     def __str__(self):
-        return '%s <%s>' % (self.author.name, self.channel.name)
+        if self.author:
+            profile_name = '%s <%s>' % (self.author.name, self.channel.name)
+        else:
+            profile_name = '%s <%s>' % (self.id_in_channel, self.channel.name)
+        return profile_name
 
 
 class ProfileAttribute(model_mixings.AttributeMixing):

src/apps/core/serializers.py

@@ -122,7 +122,7 @@ class ProfileSerializer(serializers.HyperlinkedModelSerializer):
     )
     author_id = serializers.PrimaryKeyRelatedField(
         queryset=models.Author.objects.all(),
-        write_only=True, source='author')
+        write_only=True, source='author', required=False)
     channel = serializers.HyperlinkedRelatedField(
         read_only=True,
         view_name='channel-detail'
@@ -142,10 +142,22 @@ def create(self, validated_data):
         domain_attrs = models.ProfileDomainAttribute.objects.filter(
             channel=validated_data['channel'])
         if validate_attrs(domain_attrs, attrs_data):
-            profile = models.Profile.objects.create(**validated_data)
-            for attr in attrs_data:
-                models.ProfileAttribute.objects.create(
-                    profile=profile, **attr)
+            channel = validated_data.pop('channel')
+            id_in_channel = validated_data.pop('id_in_channel')
+            profile, created = models.Profile.objects.update_or_create(
+                channel=channel, id_in_channel=id_in_channel,
+                defaults=validated_data)
+            for attr_data in attrs_data:
+                if created:
+                    models.ProfileAttribute.objects.create(
+                        profile=profile, **attr_data)
+                else:
+                    attr = models.ProfileAttribute.objects.get_or_create(
+                        profile=profile,
+                        field=attr_data['field']
+                    )[0]
+                    attr.value = attr_data['value']
+                    attr.save()
             return profile
 
     def update(self, instance, validated_data):

src/apps/core/signals.py

@@ -1,59 +1,10 @@
 from django.contrib.auth.models import User
 from django.db.models.signals import post_save
 from django.dispatch import receiver
-from django.db import transaction
 from rest_framework.authtoken.models import Token
-from apps.core.models import Manifestation
-from apps.nlp import models, pre_processing
 
 
 @receiver(post_save, sender=User)
 def create_auth_token(sender, instance=None, created=False, **kwargs):
     if created:
         Token.objects.create(user=instance)
-
-
-@receiver(post_save, sender=Manifestation)
-@transaction.atomic
-def process_manifestation(sender, instance, created, **kwargs):
-    if not created:
-        models.ManifestationToken.objects.filter(
-            manifestation=instance
-        ).delete()
-
-    bow, stem_reference = pre_processing.bow(instance.content)
-    if len(bow) > 0:
-        max_value = max(bow.values())
-        for stem, occurrences in bow.items():
-            token = models.Token.objects.get_or_create(stem=stem)[0]
-            for original_word, occurrences in stem_reference[stem].items():
-                token.add_original_word(original_word, times=occurrences)
-            token.save()
-
-            mt = models.ManifestationToken()
-            mt.manifestation = instance
-            mt.token = token
-            mt.occurrences = occurrences
-            mt.frequency = occurrences / max_value
-            mt.save()
-            print(mt)
-
-    bigram_bow, stem_reference = pre_processing.bow(instance.content, ngrams=2)
-    if len(bigram_bow) > 0:
-        max_value = max(bigram_bow.values())
-        for token, occurrences in bigram_bow.items():
-            token = models.Token.objects.get_or_create(stem=token)[0]
-            t1, t2 = token.stem.split()
-            token.add_original_word(' '.join([
-                stem_reference[t1].most_common(1)[0][0],
-                stem_reference[t2].most_common(1)[0][0]
-            ]))
-            token.bigram = True
-            token.save()
-            mt = models.ManifestationToken()
-            mt.manifestation = instance
-            mt.token = token
-            mt.occurrences = occurrences
-            mt.frequency = occurrences / max_value
-            mt.save()
-            print(mt)