Finish backend

backend/api/migrations/0004_auto_20190413_1810.py

@@ -0,0 +1,23 @@
+# Generated by Django 2.1.7 on 2019-04-13 18:10
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('api', '0003_auto_20190325_1902'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='logentry',
+            name='reaction',
+            field=models.CharField(choices=[('HA', 'Happy'), ('NE', 'Neutral'), ('TI', 'Tired'), ('AN', 'Angry'), ('SA', 'Sad')], max_length=2),
+        ),
+        migrations.AlterField(
+            model_name='recommendation',
+            name='rec_typ',
+            field=models.CharField(choices=[('PO', 'Positive'), ('NE', 'Negative'), ('AV', 'Avoidance'), ('GE', 'Generic')], max_length=2),
+        ),
+    ]

backend/api/migrations/0005_recommendation_rec_description.py

@@ -0,0 +1,18 @@
+# Generated by Django 2.1.7 on 2019-04-13 18:12
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('api', '0004_auto_20190413_1810'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='recommendation',
+            name='rec_description',
+            field=models.CharField(default='', max_length=512),
+        ),
+    ]

backend/api/migrations/0006_logentry_content_class.py

@@ -0,0 +1,19 @@
+# Generated by Django 2.1.7 on 2019-04-13 18:40
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('api', '0005_recommendation_rec_description'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='logentry',
+            name='content_class',
+            field=models.CharField(choices=[('SM', 'Small Talk'), ('OP', 'One Personal'), ('BP', 'Both Personal')], default='SM', max_length=2),
+            preserve_default=False,
+        ),
+    ]

backend/api/migrations/0007_user_has_generic_recs.py

@@ -0,0 +1,18 @@
+# Generated by Django 2.1.7 on 2019-04-14 16:05
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('api', '0006_logentry_content_class'),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name='user',
+            name='has_generic_recs',
+            field=models.BooleanField(default=False),
+        ),
+    ]

backend/api/models.py

@@ -4,6 +4,7 @@ class User(models.Model):
     id = models.AutoField(primary_key=True)
     name = models.CharField(max_length=64)
     email = models.CharField(max_length=512)
+    has_generic_recs = models.BooleanField(default=False)
 
     def __str__(self):
         return 'Person("{}")'.format(self.name)
@@ -19,11 +20,11 @@ def __str__(self):
 
 class LogEntry(models.Model):
     REACTION_CHOICES = (
-        ('ha', 'Happy'),
-        ('ne', 'Neutral'),
-        ('ti', 'Tired'),
-        ('an', 'Angry'),
-        ('sa', 'Sad'),
+        ('HA', 'Happy'),
+        ('NE', 'Neutral'),
+        ('TI', 'Tired'),
+        ('AN', 'Angry'),
+        ('SA', 'Sad'),
     )
 
     TIME_CHOICES = (
@@ -48,6 +49,12 @@ class LogEntry(models.Model):
         ('PH', 'Over The Phone'),
     )
 
+    CONTENT_CHOICES = (
+        ('SM', 'Small Talk'),
+        ('OP', 'One Personal'),
+        ('BP', 'Both Personal'),
+    )
+
     id = models.AutoField(primary_key=True)
     reaction = models.CharField(max_length=2, choices=REACTION_CHOICES)
     # Who is logged about
@@ -56,6 +63,7 @@ class LogEntry(models.Model):
     time_of_day = models.CharField(max_length=2, choices=TIME_CHOICES)
     social_context = models.CharField(max_length=2, choices=SOCIAL_CHOICES)
     interaction_medium = models.CharField(max_length=2, choices=MEDIUM_CHOICES)
+    content_class = models.CharField(max_length=2, choices=CONTENT_CHOICES)
     other_loggable_text = models.CharField(max_length=512)
 
     created_at = models.DateTimeField(auto_now_add=True)
@@ -67,9 +75,11 @@ class Recommendation(models.Model):
         ('PO', 'Positive'),
         ('NE', 'Negative'),
         ('AV', 'Avoidance'),
+        ('GE', 'Generic'),
     )
     rec_typ = models.CharField(max_length=2, choices=RECOMMENDATION_CHOICES)
     recommendation = models.CharField(max_length=128)
+    rec_description = models.CharField(max_length=512, default='')
     recommend_person = models.ForeignKey('User', models.CASCADE, related_name='recommend_person')
     about_person = models.ForeignKey('Friend', models.SET_NULL, related_name='about_person', null=True)
 

backend/api/recommender.py

@@ -0,0 +1,232 @@
+import copy
+
+from .models import User, Friend, Recommendation
+from collections import defaultdict
+
+def _create_and_save_recommendation(rec, friend_id=None):
+    r = Recommendation()
+    r.rec_typ = rec['rec_type']
+    r.recommendation = rec['recommendation']
+    r.rec_description = rec['rec_description']
+    r.recommend_person = User.objects.get(id=rec['recommend_person'])
+    if friend_id:
+        r.about_person = Friend.objects.get(id=friend_id)
+    r.save()
+
+def recommendations_from_logs(logs, user_id):
+    recommendations = {
+        "data": []
+    }
+    r = {
+        "recommend_person": user_id
+    }
+
+    user = User.objects.get(id=user_id)
+
+    total_logs = len(logs)
+    in_person = 0
+    online = 0
+    over_the_phone = 0
+
+    small_talk = defaultdict(lambda: {'small': 0, 'long': 0}) # key is friend ID
+    count_small_talk = 0
+
+    reactions = defaultdict(lambda: { # key is friend ID
+        'Happy': 0,
+        'Neutral': 0,
+        'Tired': 0,
+        'Angry': 0,
+        'Sad': 0,
+        'total': 0,
+    })
+
+    morning = 0
+    afternoon = 0
+    evening = 0
+
+    for log in logs:
+        if log.interaction_medium == 'IP':
+            in_person += 1
+        elif log.interaction_medium == 'ON':
+            online += 1
+        elif log.interaction_medium == 'PH':
+            over_the_phone += 1
+
+        if log.content_class == 'SM':
+            count_small_talk += 1
+            # TODO: need to handle null case
+            small_talk[log.loggee]['small'] += 1
+        else:
+            small_talk[log.loggee]['long'] += 1
+
+        reactions[log.loggee][log.reaction] += 1
+        reactions[log.loggee]['total'] += 1
+
+        if log.time_of_day == 'MO':
+            morning += 1
+        elif log.time_of_day == 'AF':
+            afternoon += 1
+        elif log.time_of_day == 'EV':
+            evening += 1
+
+    in_person_frac = in_person / total_logs * 100
+    if in_person_frac < 50:
+        r['rec_type'] = 'PA'
+        r["recommendation"] = "Try to have more in-person interactions."
+        r["rec_description"] = (
+            "In-person interactions allow for more control "
+            "over the interaction, like body language "
+            "and other visual cues. Online and over-the-phone "
+            "interactions should be used once a good relationship "
+            "is already built."
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+    for friend in reactions:
+        name = friend.name
+        total = reactions[friend]['total']
+        if (reactions[friend]['Happy']/total * 100) > 50:
+            r['rec_type'] = 'PO'
+            r["recommendation"] = "Spend more time with {}.".format(name)
+            r["rec_description"] = (
+                "Looks like your interactions with "
+                "this friend are typically positive - "
+                "try to have more of them!"
+            )
+            _create_and_save_recommendation(r)
+            recommendations['data'].append(copy.deepcopy(r))
+        elif (reactions[friend]['Tired']/total * 100) > 10:
+            r['rec_type'] = 'PO'
+            r["recommendation"] = "Talk to {} different times.".format(name)
+            r["rec_description"] = (
+                "It's okay to be tired! "
+                "Talk to this friend when you feel more awake, "
+                "like after your morning coffee."
+            )
+            _create_and_save_recommendation(r)
+            recommendations['data'].append(copy.deepcopy(r))
+        elif (reactions[friend]['Angry']/total * 100) > 10:
+            r['rec_type'] = 'NE'
+            r["recommendation"] = "Talk to {} less.".format(name)
+            r["rec_description"] = (
+                "If this friend makes you feel angry, "
+                "it's a good idea to re-evaluate your "
+                "relationship or the context around "
+                "interactions that make you angry."
+            )
+            _create_and_save_recommendation(r)
+            recommendations['data'].append(copy.deepcopy(r))
+        elif (reactions[friend]['Sad']/total * 100) > 10:
+            r['rec_type'] = 'AV'
+            r["recommendation"] = "Avoid talking to {}.".format(name)
+            r["rec_description"] = (
+                "People that make you feel sad "
+                "shouldn't be in your life, "
+                "it's that simple!"
+            )
+            _create_and_save_recommendation(r)
+            recommendations['data'].append(copy.deepcopy(r))
+    for friend in small_talk:
+        name = friend.name
+        small_frac = small_talk[friend]['small']/(small_talk[friend]['small'] + small_talk[friend]['long']) * 100
+        if small_frac > 50:
+            r['rec_type'] = 'AV'
+            r["recommendation"] = "Avoid small talk with {}.".format(name)
+            r["rec_description"] = (
+                "Studies have shown that having more small talk "
+                "than not has a negative impact on happiness "
+                "and interaction quality. Focus on having more "
+                "substantive conversations, especially with this "
+                "friend."
+            )
+            _create_and_save_recommendation(r)
+            recommendations['data'].append(copy.deepcopy(r))
+    morning_frac = morning / total_logs * 100
+    afternoon_frac = afternoon / total_logs * 100
+    evening_frac = evening / total_logs *  100
+    if morning_frac > 50 or afternoon_frac > 50 or evening_frac > 50:
+        r['rec_type'] = 'PO'
+        r["recommendation"] = "Spread your interactions throughout the day."
+        r["rec_description"] = (
+            "Concentrating all of your interactions "
+            "in one part of the day makes it easier "
+            "for negative ones to ruin your day "
+            "and harder ones to positively influence your "
+            "day. Remember: some people need their "
+            "coffee in the morning!"
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+    if not user.has_generic_recs:
+        user.has_generic_recs = True
+        user.save()
+        r['rec_type'] = "GE"
+
+        r["recommendation"] = "Laugh and smile when starting an interaction."
+        r["rec_description"] = (
+            "Starting a conversation with an authentic friendly "
+            "smile creates a friendly and open look that invites "
+            "contact. If the other person smiles back, "
+            "then you've already started a form of contact!"
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+
+        r["recommendation"] = "Start with a compliment."
+        r["rec_description"] = (
+            "Starting a conversation  with a compliment "
+            "is usually more interesting than  a remark "
+            "about the weather. "
+            "Pick any feature that actually interests you, "
+            "otherwise it won't come off as genuine. "
+            "Feel free to continue on the topic if they show "
+            "interest!"
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+
+        r["recommendation"] = "Use body language."
+        r["rec_description"] = (
+            "You can create an 'understanding' "
+            "without using words by mirroring "
+            "the other person's body attitude. "
+            "This typically makes relating much "
+            "easier."
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+
+        r["recommendation"] = "Evaluate and understand."
+        r["rec_description"] = (
+            "Remember to evaluate reactions from "
+            "the other person and regarding verbal "
+            "or non-verbal communication. "
+            "You should also express what "
+            "you have understood from their behavior."
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+
+        r["recommendation"] = "Use humor!"
+        r["rec_description"] = (
+            "Humor creates an open and conversational "
+            "atmosphere, but remember not to joke at "
+            "the expense of other people and respect "
+            "any other sentiments. "
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+
+        r["recommendation"] = "Open up."
+        r["rec_description"] = (
+            "You're not a reporter! The more you show "
+            "yourself, the more interested they become. "
+            "A good conversation involves being interested "
+            "in the other person as well as opening up. "
+            "Opening up makes it easier for others to "
+            "relate to you, but make sure you're authentic."
+        )
+        _create_and_save_recommendation(r)
+        recommendations['data'].append(copy.deepcopy(r))
+
+    return recommendations