Merge pull request #290 from Seluj78/279-onboarding

279 onboarding

Author: supalarry

backend/PyMatcha/routes/api/profile/images.py

@@ -29,9 +29,7 @@ def add_image_profile():
         raise BadRequestError("No file passed in request")
     if file:
         if is_primary:
-            try:
-                Image.get_multi(user_id=current_user.id, is_primary=True)
-            except ValueError:
+            if not Image.get_multi(user_id=current_user.id, is_primary=True):
                 # That means there was no primary image before
                 tmp_img = BytesIO()
                 file.save(tmp_img)

backend/PyMatcha/routes/api/recommendations.py

@@ -22,7 +22,8 @@
 from flask_jwt_extended import current_user
 from flask_jwt_extended import jwt_required
 from PyMatcha import redis
-from PyMatcha.utils.errors import NotFoundError
+from PyMatcha.utils.errors import BadRequestError
+from PyMatcha.utils.recommendations import create_user_recommendations
 from PyMatcha.utils.success import SuccessOutput
 
 recommendations_bp = Blueprint("recommendations", __name__)
@@ -33,5 +34,8 @@
 def get_recommendations():
     recommendations = redis.get(f"user_recommendations:{str(current_user.id)}")
     if not recommendations:
-        raise NotFoundError("Recommendations not calculated yet", "Please come back later")
+        create_user_recommendations(current_user)
+        recommendations = redis.get(f"user_recommendations:{str(current_user.id)}")
+        if not recommendations:
+            raise BadRequestError("User recommendations cannot be calculated")
     return SuccessOutput("recommendations", json.loads(recommendations))

backend/PyMatcha/utils/recommendations.py

@@ -0,0 +1,66 @@
+import datetime
+import json
+
+from PyMatcha import redis
+from PyMatcha.utils.match_score import _get_age_diff
+from PyMatcha.utils.match_score import _get_common_tags
+from PyMatcha.utils.match_score import _get_distance
+from PyMatcha.utils.match_score import _get_gender_query
+
+
+def default_date_converter(o):
+    if isinstance(o, datetime.datetime):
+        return o.__str__()
+
+
+def create_user_recommendations(user_to_update):
+    today = datetime.datetime.utcnow()
+    user_to_update_recommendations = []
+    if not user_to_update.birthdate:
+        return
+    if not user_to_update.geohash:
+        return
+
+    user_to_update_age = (
+        today.year
+        - user_to_update.birthdate.year
+        - ((today.month, today.day) < (user_to_update.birthdate.month, user_to_update.birthdate.day))
+    )
+    user_to_update_tags = [t.name for t in user_to_update.get_tags()]
+
+    query = _get_gender_query(user_to_update.orientation, user_to_update.gender)
+
+    if not query:
+        return
+    for user in query:
+        if user.id == user_to_update.id:
+            continue
+        score = 0
+
+        distance = _get_distance(user_to_update.geohash, user.geohash)
+        if distance:
+            score -= distance
+
+        user_age = (
+            today.year - user.birthdate.year - ((today.month, today.day) < (user.birthdate.month, user.birthdate.day))
+        )
+        age_diff = _get_age_diff(user_to_update_age, user_age)
+        score -= age_diff
+
+        user_tags = [t.name for t in user.get_tags()]
+        common_tags = _get_common_tags(user_to_update_tags, user_tags)
+        score += len(common_tags) * 2
+
+        score += user.heat_score
+
+        d = {"score": score, "common_tags": common_tags, "distance": distance}
+        d.update(user.to_dict())
+        user_to_update_recommendations.append(d)
+    user_to_update_recommendations_sorted = sorted(
+        user_to_update_recommendations, key=lambda x: x["score"], reverse=True
+    )
+    redis.set(
+        f"user_recommendations:{str(user_to_update.id)}",
+        json.dumps(user_to_update_recommendations_sorted, default=default_date_converter),
+    )
+    redis.expire(f"user_recommendations:{str(user_to_update.id)}", 3600)

backend/PyMatcha/utils/tasks.py

@@ -1,16 +1,12 @@
 import datetime
-import json
 import logging
 from math import ceil
 
 from PyMatcha import celery
 from PyMatcha import redis
 from PyMatcha.models.message import Message
 from PyMatcha.models.user import User
-from PyMatcha.utils.match_score import _get_age_diff
-from PyMatcha.utils.match_score import _get_common_tags
-from PyMatcha.utils.match_score import _get_distance
-from PyMatcha.utils.match_score import _get_gender_query
+from PyMatcha.utils.recommendations import create_user_recommendations
 
 BASE_HEAT_SCORE = 30
 LIKES_MULTIPLIER = 2
@@ -102,66 +98,11 @@ def update_offline_users():
     )
 
 
-def default_date_converter(o):
-    if isinstance(o, datetime.datetime):
-        return o.__str__()
-
-
 @celery.task
 def update_user_recommendations():
-    today = datetime.datetime.utcnow()
     count = 0
     for user_to_update in User.select_all():
-        count += 1
-        user_to_update_recommendations = []
-        if not user_to_update.birthdate:
-            continue
-        if not user_to_update.geohash:
-            continue
-
-        user_to_update_age = (
-            today.year
-            - user_to_update.birthdate.year
-            - ((today.month, today.day) < (user_to_update.birthdate.month, user_to_update.birthdate.day))
-        )
-        user_to_update_tags = [t.name for t in user_to_update.get_tags()]
-
-        query = _get_gender_query(user_to_update.orientation, user_to_update.gender)
-
-        for user in query:
-            if user.id == user_to_update.id:
-                continue
-            score = 0
-
-            distance = _get_distance(user_to_update.geohash, user.geohash)
-            if distance:
-                score -= distance
-
-            user_age = (
-                today.year
-                - user.birthdate.year
-                - ((today.month, today.day) < (user.birthdate.month, user.birthdate.day))
-            )
-            age_diff = _get_age_diff(user_to_update_age, user_age)
-            score -= age_diff
-
-            user_tags = [t.name for t in user.get_tags()]
-            common_tags = _get_common_tags(user_to_update_tags, user_tags)
-            score += len(common_tags) * 2
-
-            score += user.heat_score
-
-            d = {"score": score, "common_tags": common_tags, "distance": distance}
-            d.update(user.to_dict())
-            user_to_update_recommendations.append(d)
-        user_to_update_recommendations_sorted = sorted(
-            user_to_update_recommendations, key=lambda x: x["score"], reverse=True
-        )
-        redis.set(
-            f"user_recommendations:{str(user_to_update.id)}",
-            json.dumps(user_to_update_recommendations_sorted, default=default_date_converter),
-        )
-        redis.expire(f"user_recommendations:{str(user_to_update.id)}", 3600)
+        create_user_recommendations(user_to_update)
     return f"Successfully updated recommendations for {count} users."
 
 

frontend/src/App.vue

@@ -1,13 +1,20 @@
 <template>
-  <div id="app" class="antialiased">
+  <div id="app" class="antialiased" v-bind:style="{background: getBackground}">
     <router-view/>
   </div>
 </template>
 
 <script>
 
 export default {
-  components: {
+  computed: {
+    getBackground() {
+      const currentRoute = this.$route.name;
+      if (currentRoute === 'Onboarding') {
+        return '#FDFDFD';
+      }
+      return '#FFFFFE';
+    },
   },
 };
 </script>