From 3fd54800e01567b00877b85da70008ebcc28b7ab Mon Sep 17 00:00:00 2001
From: Mathijs Miermans <m.miermans@gmail.com>
Date: Wed, 20 Dec 2023 12:36:18 -0800
Subject: [PATCH 1/6] feat: initial implementation of New Tab scheduler

---
 Pipfile                                      |    1 +
 Pipfile.lock                                 | 3110 ++++++++++--------
 app/models/prospect_model.py                 |    8 +
 app/rankers/new_tab_scheduler.py             |   31 +
 tests/assets/json/get_prospects.json         | 2798 ++++++++++++++++
 tests/unit/rankers/test_new_tab_scheduler.py |   26 +
 6 files changed, 4628 insertions(+), 1346 deletions(-)
 create mode 100644 app/models/prospect_model.py
 create mode 100644 app/rankers/new_tab_scheduler.py
 create mode 100644 tests/assets/json/get_prospects.json
 create mode 100644 tests/unit/rankers/test_new_tab_scheduler.py

diff --git a/Pipfile b/Pipfile
index 7821bd077..7971528d8 100644
--- a/Pipfile
+++ b/Pipfile
@@ -49,6 +49,7 @@ opentelemetry-sdk-extension-aws = "*"
 opentelemetry-exporter-otlp-proto-grpc = "*"
 opentelemetry-instrumentation-aiohttp-client = "==0.41b0"
 opentelemetry-instrumentation-fastapi = "==0.41b0"
+pymoo = "*"
 
 [requires]
 python_version = "3.8"
diff --git a/Pipfile.lock b/Pipfile.lock
index 3dcfed323..ca55de9a7 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "3eca9fb4d5a07e06d1f6fa839cafe2c49125218cebed97785182e0b1450e8120"
+            "sha256": "4c86364f8d3c3787cc44675ad28152129a1d96c9e515f48ade6910cae056b285"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -16,6 +16,14 @@
         ]
     },
     "default": {
+        "about-time": {
+            "hashes": [
+                "sha256:6a538862d33ce67d997429d14998310e1dbfda6cb7d9bbfbf799c4709847fece",
+                "sha256:8bbf4c75fe13cbd3d72f49a03b02c5c7dca32169b6d49117c257e7eb3eaee341"
+            ],
+            "markers": "python_version >= '3.7' and python_version < '4'",
+            "version": "==4.2.1"
+        },
         "aio-snowplow-tracker": {
             "hashes": [
                 "sha256:449e464f0dee429699814c75106bf2d6966afa0012878d3615c08db872370a95",
@@ -26,22 +34,22 @@
         },
         "aioboto3": {
             "hashes": [
-                "sha256:11e6df5bf317e0dfc1390a29fea9e9f3afd8be99bad2cc9719d2cf44080a16fb",
-                "sha256:6f504ac312f62be5199033af97f51b20fac31df7f42c128d6643241c8e5741a9"
+                "sha256:8eae15dd52c9a43845448508ad0f912028a0a176bbd85b78e1377bb5f2a4d450",
+                "sha256:9f9e07261ddf3d6fec04dd8d5f5a55e0cb3250089f4282f7a60054495ad9699b"
             ],
             "index": "pypi",
-            "version": "==11.3.0"
+            "version": "==12.1.0"
         },
         "aiobotocore": {
             "extras": [
                 "boto3"
             ],
             "hashes": [
-                "sha256:0186e6a843364748cdbbf76ee98e9337c44f71a4e694ad1b110d5c516fbce909",
-                "sha256:4805d0140bdfa17bfc2d0ba1243c8cc4273e927201fca5cf2e497c0004a9fab7"
+                "sha256:32e632fea387acd45416c2bbc03828ee2c2a66a7dc4bd3a9bcb808dea249c469",
+                "sha256:f160497cef21cfffc1a8d4219eeb27bb7b243389c2d021a812b9c0e3fb8e2bd1"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==2.6.0"
+            "markers": "python_version >= '3.8'",
+            "version": "==2.8.0"
         },
         "aiocache": {
             "extras": [
@@ -56,96 +64,85 @@
         },
         "aiohttp": {
             "hashes": [
-                "sha256:002f23e6ea8d3dd8d149e569fd580c999232b5fbc601c48d55398fbc2e582e8c",
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-                "sha256:0912ed87fee967940aacc5306d3aa8ba3a459fcd12add0b407081fbefc931e53",
-                "sha256:0cccd1de239afa866e4ce5c789b3032442f19c261c7d8a01183fd956b1935349",
-                "sha256:0fa375b3d34e71ccccf172cab401cd94a72de7a8cc01847a7b3386204093bb47",
-                "sha256:13da35c9ceb847732bf5c6c5781dcf4780e14392e5d3b3c689f6d22f8e15ae31",
-                "sha256:14cd52ccf40006c7a6cd34a0f8663734e5363fd981807173faf3a017e202fec9",
-                "sha256:16d330b3b9db87c3883e565340d292638a878236418b23cc8b9b11a054aaa887",
-                "sha256:1bed815f3dc3d915c5c1e556c397c8667826fbc1b935d95b0ad680787896a358",
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+                "sha256:cae4c0c2ca800c793cae07ef3d40794625471040a87e1ba392039639ad61ab5b",
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+                "sha256:d737e69d193dac7296365a6dcb73bbbf53bb760ab25a3727716bbd42022e8d7a",
+                "sha256:d7481f581251bb5558ba9f635db70908819caa221fc79ee52a7f58392778c636",
+                "sha256:df9cf74b9bc03d586fc53ba470828d7b77ce51b0582d1d0b5b2fb673c0baa32d",
+                "sha256:e1f80197f8b0b846a8d5cf7b7ec6084493950d0882cc5537fb7b96a69e3c8590",
+                "sha256:ecca113f19d5e74048c001934045a2b9368d77b0b17691d905af18bd1c21275e",
+                "sha256:ee2527134f95e106cc1653e9ac78846f3a2ec1004cf20ef4e02038035a74544d",
+                "sha256:f27fdaadce22f2ef950fc10dcdf8048407c3b42b73779e48a4e76b3c35bca26c",
+                "sha256:f694dc8a6a3112059258a725a4ebe9acac5fe62f11c77ac4dcf896edfa78ca28",
+                "sha256:f800164276eec54e0af5c99feb9494c295118fc10a11b997bbb1348ba1a52065",
+                "sha256:ffcd828e37dc219a72c9012ec44ad2e7e3066bec6ff3aaa19e7d435dbf4032ca"
             ],
             "index": "pypi",
-            "version": "==3.8.6"
+            "version": "==3.9.1"
         },
         "aioitertools": {
             "hashes": [
@@ -171,6 +168,14 @@
             "markers": "python_version >= '3.7'",
             "version": "==1.3.1"
         },
+        "alive-progress": {
+            "hashes": [
+                "sha256:347220c1858e3abe137fa0746895668c04df09c5261a13dc03f05795e8a29be5",
+                "sha256:42e399a66c8150dc507602dff7b7953f105ef11faf97ddaa6d27b1cbf45c4c98"
+            ],
+            "markers": "python_version >= '3.7' and python_version < '4'",
+            "version": "==3.1.5"
+        },
         "anyio": {
             "hashes": [
                 "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780",
@@ -200,7 +205,7 @@
                 "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f",
                 "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"
             ],
-            "markers": "python_version >= '3.7'",
+            "markers": "python_version < '3.11'",
             "version": "==4.0.3"
         },
         "attrs": {
@@ -211,6 +216,13 @@
             "markers": "python_version >= '3.7'",
             "version": "==23.1.0"
         },
+        "autograd": {
+            "hashes": [
+                "sha256:208dde2a938e63b4f8f5049b1985505139e529068b0d26f8cd7771fd3eb145d5",
+                "sha256:8731e08a0c4e389d8695a40072ada4512641c113b6cace8f4cfbe8eb7e9aedeb"
+            ],
+            "version": "==1.6.2"
+        },
         "backoff": {
             "hashes": [
                 "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba",
@@ -221,122 +233,26 @@
         },
         "boto3": {
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+                "sha256:1fe5fa75ff0f0c29a6f55e818d149d33571731e692a7b785ded7a28ac832cae8",
+                "sha256:fa5aa92d16763cb906fb4a83d6eba887342202a980bea07862af5ba40827aa5a"
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-            "version": "==1.28.17"
+            "version": "==1.33.1"
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         "botocore": {
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-                "sha256:6ac34a1d34aa3750e78b77b8596617e2bab938964694d651939dba2cbde2c12b"
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             "markers": "python_version >= '3.7'",
-            "version": "==1.31.17"
+            "version": "==1.33.1"
         },
         "certifi": {
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-            "markers": "python_full_version >= '3.7.0'",
-            "version": "==3.3.0"
+            "version": "==2023.11.17"
         },
         "click": {
             "hashes": [
@@ -346,6 +262,79 @@
             "markers": "python_version >= '3.7'",
             "version": "==8.1.7"
         },
+        "cma": {
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@@ -354,96 +343,175 @@
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             "hashes": [
@@ -453,6 +521,12 @@
             "index": "pypi",
             "version": "==3.4.1"
         },
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@@ -614,63 +688,64 @@
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+            "version": "==0.6.1"
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@@ -682,27 +757,27 @@
         },
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@@ -714,19 +789,129 @@
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@@ -772,6 +957,59 @@
             "markers": "python_version >= '3.8'",
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@@ -1006,6 +1244,66 @@
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@@ -1016,22 +1314,20 @@
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@@ -1077,10 +1373,40 @@
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@@ -1177,131 +1503,131 @@
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@@ -1332,19 +1658,19 @@
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@@ -1377,11 +1703,11 @@
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@@ -1937,7 +2323,7 @@
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@@ -1969,264 +2355,280 @@
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@@ -2427,11 +2829,11 @@
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@@ -2443,11 +2845,11 @@
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@@ -2459,11 +2861,11 @@
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@@ -2507,107 +2909,123 @@
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+                "sha256:db8e58b9d79200c76956cefd14d5c90af54416ff5353c5bfd7cbe58818e26ef0",
+                "sha256:ddb2a5c08a4eaaba605340fdee8fc08e406c56617566d9643ad8bf6852778fc7",
+                "sha256:e0381b4ce23ff92f8170080c97678040fc5b08da85e9e292292aba67fdac6c34",
+                "sha256:e23a6d84d9d1738dbc6e38167776107e63307dfc8ad108e580548d1f2c587f42",
+                "sha256:e516dc8baf7b380e6c1c26792610230f37147bb754d6426462ab115a02944385",
+                "sha256:ea65804b5dc88dacd4a40279af0cdadcfe74b3e5b4c897aa0d81cf86927fee78",
+                "sha256:ec61d826d80fc293ed46c9dd26995921e3a82146feacd952ef0757236fc137be",
+                "sha256:ee04010f26d5102399bd17f8df8bc38dc7ccd7701dc77f4a68c5b8d733406958",
+                "sha256:f3bc6af6e2b8f92eced34ef6a96ffb248e863af20ef4fde9448cc8c9b858b749",
+                "sha256:f7d6b36dd2e029b6bcb8a13cf19664c7b8e19ab3a58e0fefbb5b8461447ed5ec"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==1.9.2"
+            "version": "==1.9.4"
         }
     }
 }
diff --git a/app/models/prospect_model.py b/app/models/prospect_model.py
new file mode 100644
index 000000000..7a3e7f6f7
--- /dev/null
+++ b/app/models/prospect_model.py
@@ -0,0 +1,8 @@
+from pydantic import BaseModel
+
+
+class ProspectModel(BaseModel):
+    id: str
+    topic: str
+    publisher: str
+    url: str
diff --git a/app/rankers/new_tab_scheduler.py b/app/rankers/new_tab_scheduler.py
new file mode 100644
index 000000000..e663f83fc
--- /dev/null
+++ b/app/rankers/new_tab_scheduler.py
@@ -0,0 +1,31 @@
+from pymoo.core.problem import ElementwiseProblem
+
+
+class ArticleSelectionProblem(ElementwiseProblem):
+    def __init__(self, articles, n_articles=30):
+        super().__init__(n_var=len(articles), n_obj=1, n_constr=1 + 2 * len(set([a.topic for a in articles])))
+        self.articles = articles
+        self.n_articles = n_articles
+
+    def _evaluate(self, x, out, *args, **kwargs):
+        selected_articles = [article for article, flag in zip(self.articles, x) if flag == 1]
+
+        # Objective: Maximize total quality score
+        total_quality_score = sum(article.quality_score for article in selected_articles)
+        out["F"] = -total_quality_score  # Negative because we want to maximize
+
+        # Constraints
+        topic_count = {}
+        publisher_count = {}
+        for article in selected_articles:
+            topic_count[article.topic] = topic_count.get(article.topic, 0) + 1
+            publisher_count[article.publisher] = publisher_count.get(article.publisher, 0) + 1
+
+        # Constraint: No more than 2 articles from the same topic or publisher
+        topic_constraints = [count - 2 for count in topic_count.values()]
+        publisher_constraints = [count - 2 for count in publisher_count.values()]
+
+        # Constraint: Exactly 30 articles
+        article_count_constraint = [len(selected_articles) - self.n_articles]
+
+        out["G"] = topic_constraints + publisher_constraints + article_count_constraint
diff --git a/tests/assets/json/get_prospects.json b/tests/assets/json/get_prospects.json
new file mode 100644
index 000000000..339d0d11b
--- /dev/null
+++ b/tests/assets/json/get_prospects.json
@@ -0,0 +1,2798 @@
+{
+  "data": {
+    "getProspects": [
+      {
+        "id": "ffba8b78-1b0a-4835-a224-682df208db94",
+        "prospectId": "05ba962e-5cbe-51d2-91bb-09b08f0ac638",
+        "scheduledSurfaceGuid": "NEW_TAB_EN_US",
+        "topic": "",
+        "prospectType": "RSS_LOGISTIC_RECENT",
+        "url": "https://www.vanityfair.com/hollywood/conan-obriens-wild-first-year-an-oral-history",
+        "createdAt": 1703095880,
+        "imageUrl": "https://media.vanityfair.com/photos/6579e0749adb7e7317b91d55/16:9/w_1280,c_limit/VF0224-Conan-Obrien.jpg",
+        "authors": "Andrew Buss",
+        "publisher": "Vanity Fair",
+        "domain": "vanityfair.com",
+        "title": "Conan O’Brien’s Wild First Year at ‘Late Night’",
+        "excerpt": "If you tuned in to NBC at 12:35 a.m. on September 13, 1993, you witnessed late-night history in the making. Jay Leno had inherited The Tonight Show from Johnny Carson in 1992, and a deeply pissed-off David Letterman had decamped to CBS. That meant a new host for Late Night had to be found.",
+        "language": "EN",
+        "saveCount": 0,
+        "isSyndicated": false,
+        "isCollection": false,
+        "approvedCorpusItem": null,
+        "rejectedCorpusItem": null,
+        "item": {
+          "givenUrl": "https://www.vanityfair.com/hollywood/conan-obriens-wild-first-year-an-oral-history",
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+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          2,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          2,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          3,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          3,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          4,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          5,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          6,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          6,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          7,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          7,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          8,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          8,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          9,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          9,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          10,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          10,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          11,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          12,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          12,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          13,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          13,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          14,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          14,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          15,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          15,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          16,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          16,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          17,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          17,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          18,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          18,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          19,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          19,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          20,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          20,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          21,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          21,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          22,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          22,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          23,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          23,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          24,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          24,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          25,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          25,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          26,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          26,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          27,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          27,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          28,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          28,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          29,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          29,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          30,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          30,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          31,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          31,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          32,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          33,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          33,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          34,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          34,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          35,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          35,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          36,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          36,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          37,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          37,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          38,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          38,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          39,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          39,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          40,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          40,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          41,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          41,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          42,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          42,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          43,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          43,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          44,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          44,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          45,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          46,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          46,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          47,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          47,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          48,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          48,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          49,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          49,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      }
+    ]
+  }
+}
diff --git a/tests/unit/rankers/test_new_tab_scheduler.py b/tests/unit/rankers/test_new_tab_scheduler.py
new file mode 100644
index 000000000..fec854fe6
--- /dev/null
+++ b/tests/unit/rankers/test_new_tab_scheduler.py
@@ -0,0 +1,26 @@
+import json
+import os
+
+from pymoo.optimize import minimize
+from pymoo.algorithms.soo.nonconvex.ga import GA
+
+from app.config import ROOT_DIR
+from app.models.prospect_model import ProspectModel
+from app.rankers.new_tab_scheduler import ArticleSelectionProblem
+
+
+def test_new_tab_scheduler():
+    with open(os.path.join(ROOT_DIR, 'tests/assets/json/get_prospects.json')) as fp:
+        data = json.load(fp)
+
+    articles = [ProspectModel(**a) for a in data['data']['getProspects']]
+
+    problem = ArticleSelectionProblem(articles)
+
+    algorithm = GA(pop_size=len(articles))  # JSON fixture has 50 articles
+
+    res = minimize(problem, algorithm, termination=('n_gen', 50))
+
+    # Decode the solution
+    selected_articles = [article for article, flag in zip(articles, res.X) if flag == 1]
+    print(selected_articles)

From ff057092e1e62499c87a51b920845b4c573113ce Mon Sep 17 00:00:00 2001
From: Mathijs Miermans <m.miermans@gmail.com>
Date: Thu, 21 Dec 2023 11:03:20 -0800
Subject: [PATCH 2/6] feat: new_tab_scheduler balances topics and publishers

---
 app/models/prospect_model.py                 |    1 +
 app/rankers/new_tab_scheduler.py             |   79 +-
 tests/assets/json/get_prospects.json         | 2020 +++++++++---------
 tests/unit/rankers/test_new_tab_scheduler.py |   36 +-
 4 files changed, 1048 insertions(+), 1088 deletions(-)

diff --git a/app/models/prospect_model.py b/app/models/prospect_model.py
index 7a3e7f6f7..a04c88de6 100644
--- a/app/models/prospect_model.py
+++ b/app/models/prospect_model.py
@@ -6,3 +6,4 @@ class ProspectModel(BaseModel):
     topic: str
     publisher: str
     url: str
+    quality_score: float
diff --git a/app/rankers/new_tab_scheduler.py b/app/rankers/new_tab_scheduler.py
index e663f83fc..895d0357f 100644
--- a/app/rankers/new_tab_scheduler.py
+++ b/app/rankers/new_tab_scheduler.py
@@ -1,31 +1,64 @@
-from pymoo.core.problem import ElementwiseProblem
+from typing import List
 
+import numpy as np
+from pymoo.algorithms.soo.nonconvex.ga import GA
+from pymoo.core.problem import Problem
+from pymoo.operators.crossover.pntx import TwoPointCrossover
+from pymoo.operators.mutation.bitflip import BitflipMutation
+from pymoo.operators.sampling.rnd import BinaryRandomSampling
+from pymoo.optimize import minimize
 
-class ArticleSelectionProblem(ElementwiseProblem):
-    def __init__(self, articles, n_articles=30):
-        super().__init__(n_var=len(articles), n_obj=1, n_constr=1 + 2 * len(set([a.topic for a in articles])))
-        self.articles = articles
-        self.n_articles = n_articles
+from app.models.prospect_model import ProspectModel
 
-    def _evaluate(self, x, out, *args, **kwargs):
-        selected_articles = [article for article, flag in zip(self.articles, x) if flag == 1]
 
-        # Objective: Maximize total quality score
-        total_quality_score = sum(article.quality_score for article in selected_articles)
-        out["F"] = -total_quality_score  # Negative because we want to maximize
+DEFAULT_DUPLICATE_LIMIT = 2
+
+
+class ArticleSelectionProblem(Problem):
+    def __init__(self, articles: List[ProspectModel], n_articles=30):
+        n_items = len(articles)
+        self.P = np.array([a.quality_score for a in articles])
+
+        all_topics = sorted({a.topic for a in articles})
+        all_publishers = sorted({a.publisher for a in articles})
+
+        # Create topic matrix
+        topic_matrix = np.zeros((n_items, len(all_topics)))
+        for i, article in enumerate(articles):
+            topic_index = all_topics.index(article.topic)
+            topic_matrix[i, topic_index] = 1
+
+        # Create publisher matrix
+        publisher_matrix = np.zeros((n_items, len(all_publishers)))
+        for i, article in enumerate(articles):
+            publisher_index = all_publishers.index(article.publisher)
+            publisher_matrix[i, publisher_index] = 1
+
+        # Concatenate topic and publisher matrices
+        self.W = np.hstack((topic_matrix, publisher_matrix))
+        n_constraints = self.W.shape[1]  # equal to len(all_topics) + len(all_publishers)
+
+        self.duplicate_limit = DEFAULT_DUPLICATE_LIMIT  # Maximum duplicate topics and publishers
+
+        super().__init__(n_var=n_items, n_obj=1, n_ieq_constr=n_constraints, xl=0, xu=1, vtype=bool)
+
+    def _evaluate(self, x, out, *args, **kwargs):
+        out["F"] = -np.sum(self.P * x, axis=1)
+        out["G"] = np.dot(x, self.W) - self.duplicate_limit
 
-        # Constraints
-        topic_count = {}
-        publisher_count = {}
-        for article in selected_articles:
-            topic_count[article.topic] = topic_count.get(article.topic, 0) + 1
-            publisher_count[article.publisher] = publisher_count.get(article.publisher, 0) + 1
 
-        # Constraint: No more than 2 articles from the same topic or publisher
-        topic_constraints = [count - 2 for count in topic_count.values()]
-        publisher_constraints = [count - 2 for count in publisher_count.values()]
+class ArticleSelectionAlgorithm(GA):
+    def __init__(self, articles):
+        super().__init__(
+            pop_size=len(articles),
+            sampling=BinaryRandomSampling(),
+            crossover=TwoPointCrossover(),
+            mutation=BitflipMutation(),
+            eliminate_duplicates=True)
 
-        # Constraint: Exactly 30 articles
-        article_count_constraint = [len(selected_articles) - self.n_articles]
 
-        out["G"] = topic_constraints + publisher_constraints + article_count_constraint
+def select_articles(prospects: List[ProspectModel], n_gen=100) -> List[ProspectModel]:
+    problem = ArticleSelectionProblem(prospects)
+    algorithm = ArticleSelectionAlgorithm(prospects)
+    res = minimize(problem, algorithm, verbose=True, termination=('n_gen', n_gen))
+    return [article for article, is_selected in zip(prospects, res.X) if is_selected]
diff --git a/tests/assets/json/get_prospects.json b/tests/assets/json/get_prospects.json
index 339d0d11b..052817d8a 100644
--- a/tests/assets/json/get_prospects.json
+++ b/tests/assets/json/get_prospects.json
@@ -2,1649 +2,1501 @@
   "data": {
     "getProspects": [
       {
-        "id": "ffba8b78-1b0a-4835-a224-682df208db94",
-        "prospectId": "05ba962e-5cbe-51d2-91bb-09b08f0ac638",
+        "id": "80705a92-0b35-4cc6-af47-798955351f53",
+        "prospectId": "32e50e71-c2da-571b-8dc9-458380bf8314",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://www.vanityfair.com/hollywood/conan-obriens-wild-first-year-an-oral-history",
-        "createdAt": 1703095880,
-        "imageUrl": "https://media.vanityfair.com/photos/6579e0749adb7e7317b91d55/16:9/w_1280,c_limit/VF0224-Conan-Obrien.jpg",
-        "authors": "Andrew Buss",
-        "publisher": "Vanity Fair",
-        "domain": "vanityfair.com",
-        "title": "Conan O’Brien’s Wild First Year at ‘Late Night’",
-        "excerpt": "If you tuned in to NBC at 12:35 a.m. on September 13, 1993, you witnessed late-night history in the making. Jay Leno had inherited The Tonight Show from Johnny Carson in 1992, and a deeply pissed-off David Letterman had decamped to CBS. That meant a new host for Late Night had to be found.",
+        "topic": "TRAVEL",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.theatlantic.com/family/archive/2023/12/large-multigenerational-family-vacation-parents-relatives/676382/",
+        "createdAt": 1703036692,
+        "imageUrl": "https://cdn.theatlantic.com/thumbor/b4xP_wDgticMrGkx7rG1eGLJvvk=/0x43:2000x1085/1200x625/media/img/mt/2023/12/multigenerational_vacation/original.jpg",
+        "authors": "Michael Waters",
+        "publisher": "The Atlantic",
+        "domain": "theatlantic.com",
+        "title": "The New Family Vacation",
+        "excerpt": "More and more Americans are traveling with multiple generations—and, perhaps, learning who their relatives really are.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 150,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://www.vanityfair.com/hollywood/conan-obriens-wild-first-year-an-oral-history",
-          "itemId": "3982855609",
-          "normalUrl": "http://vanityfair.com/hollywood/conan-obriens-wild-first-year-an-oral-history",
-          "datePublished": "2023-12-20 07:00:00",
-          "timeToRead": 27,
+          "givenUrl": "https://www.theatlantic.com/family/archive/2023/12/large-multigenerational-family-vacation-parents-relatives/676382/",
+          "itemId": "3981845992",
+          "normalUrl": "http://theatlantic.com/family/archive/2023/12/large-multigenerational-family-vacation-parents-relatives/676382",
+          "datePublished": "2023-12-18 06:00:00",
+          "timeToRead": 5,
           "__typename": "Item"
         },
         "__typename": "Prospect"
       },
       {
-        "id": "a2472bfe-6bd5-4e7d-9320-d0206a086400",
-        "prospectId": "99b0edcc-425f-5962-b7a7-4883fd2cf058",
+        "id": "108a7b32-548d-4a04-9a72-acdf02819559",
+        "prospectId": "db67c9db-5289-5ebb-af8b-8e3712aa8042",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://www.npr.org/2023/12/20/1220559009/congolese-head-to-the-polls-to-elect-their-next-president",
-        "createdAt": 1703095880,
-        "imageUrl": "https://media.npr.org/include/images/facebook-default-wide-s1400-c100.jpg",
-        "authors": "Michel Martin,Emmanuel Akinwotu",
-        "publisher": "NPR",
-        "domain": "npr.org",
-        "title": "Congolese head to the polls to elect their next president",
-        "excerpt": "Millions of Congolese will vote for a new president Wednesday, with hopes for a peaceful election. The Democratic Republic of Congo has vast mineral wealth, but is impacted by poverty and conflict.",
+        "topic": "ENTERTAINMENT",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.theringer.com/movies/2023/12/14/24001087/netflix-2023-streaming-wars",
+        "createdAt": 1703036692,
+        "imageUrl": "https://cdn.vox-cdn.com/thumbor/l8YrsAtQ2KKcObtEEz037hpSbKU=/0x0:1200x800/1400x1050/filters:focal(504x304:696x496):no_upscale()/cdn.vox-cdn.com/uploads/chorus_image/image/72962110/netflix_getty_ringer.0.jpg",
+        "authors": "A.A. Dowd",
+        "publisher": "The Ringer",
+        "domain": "theringer.com",
+        "title": "The Year Netflix Ended the Streaming Wars",
+        "excerpt": "After a shaky 2022 in which it seemed like the competition was finally getting to Netflix, the company proved time and time again in 2023 that it has a hold on viewers like no other The critics have spoken and they mostly agree: Succession was the TV show of 2023.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 127,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://www.npr.org/2023/12/20/1220559009/congolese-head-to-the-polls-to-elect-their-next-president",
-          "itemId": "3982793091",
-          "normalUrl": "http://npr.org/2023/12/20/1220559009/congolese-head-to-the-polls-to-elect-their-next-president",
-          "datePublished": "2023-12-20 00:00:00",
-          "timeToRead": null,
+          "givenUrl": "https://www.theringer.com/movies/2023/12/14/24001087/netflix-2023-streaming-wars",
+          "itemId": "3980081318",
+          "normalUrl": "http://theringer.com/movies/2023/12/14/24001087/netflix-2023-streaming-wars",
+          "datePublished": "2023-12-14 08:00:00",
+          "timeToRead": 15,
           "__typename": "Item"
         },
         "__typename": "Prospect"
       },
       {
-        "id": "d737ba90-3638-4db0-8245-cb7522c2db42",
-        "prospectId": "6a4115cc-96e5-5b6b-b7a0-9639def8d58c",
+        "id": "7d6abf2f-7602-40b3-87b7-c761cb825c02",
+        "prospectId": "a2fc2568-bcdc-514a-881f-e1091de28e9f",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://nymag.com/intelligencer/2023/12/rudy-giuliani-is-really-really-broke.html",
-        "createdAt": 1703095880,
-        "imageUrl": "https://pyxis.nymag.com/v1/imgs/2c3/69b/304e99ff5f5885b27f354ee3341245ae94-giuliani.1x.rsocial.w1200.jpg",
-        "authors": "Nia Prater",
-        "publisher": "New York Magazine",
-        "domain": "nymag.com",
-        "title": "Rudy Is Really, Really Broke",
-        "excerpt": "In 2021, federal agents raided Rudy Giuliani’s home and office and seized his electronic devices as part of an inquiry into his dealings with Ukraine.",
+        "topic": "SCIENCE",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.wired.com/story/oh-good-hurricanes-are-now-made-of-microplastics/",
+        "createdAt": 1703036692,
+        "imageUrl": "https://media.wired.com/photos/657b9caf2b6469ecccd5b269/191:100/w_1280,c_limit/hurricanelarry-science-2H1JPD1.jpg",
+        "authors": "Matt Simon",
+        "publisher": "WIRED",
+        "domain": "wired.com",
+        "title": "Oh Good, Hurricanes Are Now Made of Microplastics",
+        "excerpt": "As Hurricane Larry curved north in the Atlantic in 2021, sparing the eastern seaboard of the United States, a special instrument was waiting for it on the coast of Newfoundland.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 100,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://nymag.com/intelligencer/2023/12/rudy-giuliani-is-really-really-broke.html",
-          "itemId": "3982967943",
-          "normalUrl": "http://nymag.com/intelligencer/2023/12/rudy-giuliani-is-really-really-broke.html",
-          "datePublished": "2023-12-20 11:06:33",
-          "timeToRead": 2,
+          "givenUrl": "https://www.wired.com/story/oh-good-hurricanes-are-now-made-of-microplastics/",
+          "itemId": "3981839912",
+          "normalUrl": "http://wired.com/story/oh-good-hurricanes-are-now-made-of-microplastics",
+          "datePublished": "2023-12-18 07:00:00",
+          "timeToRead": 5,
           "__typename": "Item"
         },
         "__typename": "Prospect"
       },
       {
-        "id": "198d2c90-3adb-4f16-95de-85d0d1011796",
-        "prospectId": "9355b362-2715-53d3-ae5f-664935efc599",
+        "id": "d32110e5-e852-4192-b231-38003deca5fc",
+        "prospectId": "9ddc363f-09cc-5228-9dd3-f2a4ce4602ad",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://www.cntraveler.com/story/where-you-should-travel-in-2024-according-to-your-sign",
-        "createdAt": 1703095880,
-        "imageUrl": "https://media.cntraveler.com/photos/6582078d3ac3bbf39799b40f/16:9/w_1280,c_limit/Guatemala_GettyImages-522674810.jpg",
-        "authors": "Steph Koyfman",
-        "publisher": "Condé Nast Traveler",
-        "domain": "cntraveler.com",
-        "title": "Where You Should Travel in 2024, According to Your Sign",
-        "excerpt": "After the year of revenge travel (and flight costs rising with a similar vengeance), tourism might be settling into relative homeostasis in 2024. Then again, everything has changed, including the terrain of where you’ll want to go next, and maybe even the order of your bucket list.",
+        "topic": "PERSONAL_FINANCE",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.entrepreneur.com/starting-a-business/7-internet-based-home-businesses-to-start-in-2024/466068",
+        "createdAt": 1703036692,
+        "imageUrl": "https://assets.entrepreneur.com/content/3x2/2000/1702329660-passive-income-options-2024-1223-g1070097534.jpg?format=pjeg&auto=webp",
+        "authors": "Chris D. Bentley",
+        "publisher": "Entrepreneur",
+        "domain": "entrepreneur.com",
+        "title": "7 Internet Based Home Businesses to Start in 2024",
+        "excerpt": "It is no secret that many people are struggling to get through these current economic times, but with just a laptop, webcam, strong internet connection and some effort, you can earn some extra money working from home.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 113,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
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+        "imageUrl": "https://cdn.vox-cdn.com/thumbor/gfzPMrNEBbWJYz1wwmiAgcN_VMw=/0x0:3600x2400/1200x628/filters:focal(1805x825:1806x826)/cdn.vox-cdn.com/uploads/chorus_asset/file/25166630/GAG_203_Unit_00205RC.jpg",
+        "authors": "Alex Cranz",
+        "publisher": "The Verge",
+        "domain": "theverge.com",
+        "title": "The gulf between the real world and streaming has never been wider",
+        "excerpt": "Stop me if you’ve heard this one. You’re at a holiday gathering and some very offline family member starts chatting about the show Yellowstone.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 177,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://www.vanityfair.com/style/meet-queen-camillas-children",
-          "itemId": "3982047097",
-          "normalUrl": "http://vanityfair.com/style/meet-queen-camillas-children",
-          "datePublished": "2023-12-18 12:41:47",
-          "timeToRead": 11,
+          "givenUrl": "https://www.theverge.com/24003126/netflix-viewing-data-ginny-georgia-witcher",
+          "itemId": "3981076880",
+          "normalUrl": "http://theverge.com/24003126/netflix-viewing-data-ginny-georgia-witcher",
+          "datePublished": "2023-12-16 10:00:00",
+          "timeToRead": 5,
           "__typename": "Item"
         },
         "__typename": "Prospect"
       },
       {
-        "id": "07fc5b04-514b-407f-81ef-453f9a823b94",
-        "prospectId": "5da7a9f8-7de1-59b9-919e-77d3caff4f6c",
+        "id": "0c24541b-04db-4890-b419-cd106694f162",
+        "prospectId": "6ed5d6b4-f561-5156-a317-e50b1064dc50",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://www.gq.com/story/best-watches-of-2023-according-to-experts",
-        "createdAt": 1703095887,
-        "imageUrl": "https://media.gq.com/photos/6581f3a9e005bed660f529ba/16:9/w_1280,c_limit/CORRECT%20-%202023%20Watch%20of%20the%20Year%20(1).jpg",
-        "authors": "Cam Wolf",
-        "publisher": "GQ",
-        "domain": "gq.com",
-        "title": "The Best Watch of 2023, According to the Watch Illuminati",
-        "excerpt": "On Friday, I shared the first part of GQ’s annual Watch Survey, in which our panel of 46 mega collectors, retailers, vintage dealers, auction-house specialists, journalists, and influencers weighed in on the best watch brands of 2023.",
+        "topic": "HEALTH_FITNESS",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.nytimes.com/2023/12/13/well/move/cadaver-workshops-yoga-massage-therapy.html",
+        "createdAt": 1703036704,
+        "imageUrl": "https://static01.nyt.com/images/2023/12/06/multimedia/06FITNESS-DISSECTION10-lmzp/06FITNESS-DISSECTION10-lmzp-facebookJumbo.jpg",
+        "authors": "Danielle Friedman",
+        "publisher": "The New York Times",
+        "domain": "nytimes.com",
+        "title": "Why Yoga Teachers Are Learning to Dissect Cadavers",
+        "excerpt": "Jane Sato thought she understood the abdominal muscles. For the first decade that she taught Pilates and yoga in New York City, she would tell her students to pull their belly button into their spine to strengthen their core.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 132,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://www.gq.com/story/best-watches-of-2023-according-to-experts",
-          "itemId": "3982868186",
-          "normalUrl": "http://gq.com/story/best-watches-of-2023-according-to-experts",
-          "datePublished": "2023-12-20 06:55:00",
-          "timeToRead": 8,
+          "givenUrl": "https://www.nytimes.com/2023/12/13/well/move/cadaver-workshops-yoga-massage-therapy.html",
+          "itemId": "3979670055",
+          "normalUrl": "http://nytimes.com/2023/12/13/well/move/cadaver-workshops-yoga-massage-therapy.html",
+          "datePublished": "2023-12-13 09:58:22",
+          "timeToRead": 7,
           "__typename": "Item"
         },
         "__typename": "Prospect"
       },
       {
-        "id": "f2b73894-3f3e-4ca6-8820-fe5cfdc6449c",
-        "prospectId": "9de73a2f-5e5c-5af8-ac8f-38bf9bfa5433",
+        "id": "0d011d76-57cb-4a60-a986-97598ccdf9c1",
+        "prospectId": "6ea8f26f-1e2d-5bec-8167-12db3a14d34d",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://omny.fm/shows/bloomberg-daybreak/tensions-rise-in-red-sea-apple-races-to-fix-smartw",
-        "createdAt": 1703095887,
-        "imageUrl": "https://omny.fm/shows/bloomberg-daybreak/tensions-rise-in-red-sea-apple-races-to-fix-smartw/image.jpg?t=1673277911&size=wideShare",
-        "authors": "",
-        "publisher": "omny.fm",
-        "domain": "omny.fm",
-        "title": "Tensions Rise in Red Sea; Apple Races to Fix SmartWatch",
-        "excerpt": "Bloomberg Daybreak: US Edition 807 clip(s)",
+        "topic": "POLITICS",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.theatlantic.com/podcasts/archive/2023/12/how-trump-could-manipulate-military/676341/",
+        "createdAt": 1703036704,
+        "imageUrl": "https://cdn.theatlantic.com/thumbor/-g59nPhhfU9AkbkbzySI9Kx6puI=/0x0:2995x1560/1200x625/media/img/mt/2023/12/GettyImages_1174363076/original.jpg",
+        "authors": "Hanna Rosin",
+        "publisher": "The Atlantic",
+        "domain": "theatlantic.com",
+        "title": "How Trump Could Manipulate the Military",
+        "excerpt": "It’s surprisingly easy. When my colleague Tom Nichols, who taught at the Naval War College for 25 years, warns people that Donald Trump might be a threat to democracy, they often ask him to prove it.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 123,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://omny.fm/shows/bloomberg-daybreak/tensions-rise-in-red-sea-apple-races-to-fix-smartw",
-          "itemId": "3982341165",
-          "normalUrl": "http://omny.fm/shows/bloomberg-daybreak/tensions-rise-in-red-sea-apple-races-to-fix-smartw",
-          "datePublished": null,
-          "timeToRead": null,
+          "givenUrl": "https://www.theatlantic.com/podcasts/archive/2023/12/how-trump-could-manipulate-military/676341/",
+          "itemId": "3980180874",
+          "normalUrl": "http://theatlantic.com/podcasts/archive/2023/12/how-trump-could-manipulate-military/676341",
+          "datePublished": "2023-12-14 11:00:05",
+          "timeToRead": 19,
           "__typename": "Item"
         },
         "__typename": "Prospect"
       },
       {
-        "id": "5c57c25a-faa7-47d1-b548-b5dc342c6bb0",
-        "prospectId": "e30c9b76-fdb4-5611-97d3-6de7443be434",
+        "id": "d7ffe869-777e-4b46-8807-bd7946b5f8a4",
+        "prospectId": "4bb8485a-d83a-5633-9242-263d255dc356",
         "scheduledSurfaceGuid": "NEW_TAB_EN_US",
-        "topic": "",
-        "prospectType": "RSS_LOGISTIC_RECENT",
-        "url": "https://www.self.com/story/feeling-cranky-tips",
-        "createdAt": 1703095888,
-        "imageUrl": "https://media.self.com/photos/65809458875ae6ca80018655/2:1/w_1280,c_limit/Cranky%20tips.png",
-        "authors": "Julia Ries",
-        "publisher": "SELF",
-        "domain": "self.com",
-        "title": "What to Do When You’re Super Cranky and Hate Everyone",
-        "excerpt": "Once in a while, I wake up inexplicably cranky. There’s nothing specifically wrong, per se. It’s just that, for whatever reason, everyone around me gets on my nerves.",
+        "topic": "HEALTH_FITNESS",
+        "prospectType": "TIMESPENT_MODELED",
+        "url": "https://www.nytimes.com/2023/12/14/well/move/5-minute-hiit-workout.html",
+        "createdAt": 1703036705,
+        "imageUrl": "https://static01.nyt.com/images/2023/12/19/well/12SCAM-MICRO-WORKOUT/12SCAM-MICRO-WORKOUT-facebookJumbo-v2.jpg",
+        "authors": "Cindy Kuzma",
+        "publisher": "The New York Times",
+        "domain": "nytimes.com",
+        "title": "What Good Is a 5-Minute Workout, Really?",
+        "excerpt": "A few lucky people find a fitness routine they love and stick to it. But many of us simply want to get our workout over with as quickly as possible. For those in the latter camp, it’s hard to resist headlines claiming we can get in shape in five minutes or less per day.",
         "language": "EN",
-        "saveCount": 0,
+        "saveCount": 168,
         "isSyndicated": false,
         "isCollection": false,
         "approvedCorpusItem": null,
         "rejectedCorpusItem": null,
         "item": {
-          "givenUrl": "https://www.self.com/story/feeling-cranky-tips",
-          "itemId": "3982887291",
-          "normalUrl": "http://self.com/story/feeling-cranky-tips",
-          "datePublished": "2023-12-20 08:00:00",
-          "timeToRead": 6,
+          "givenUrl": "https://www.nytimes.com/2023/12/14/well/move/5-minute-hiit-workout.html",
+          "itemId": "3980157449",
+          "normalUrl": "http://nytimes.com/2023/12/14/well/move/5-minute-hiit-workout.html",
+          "datePublished": "2023-12-14 10:00:12",
+          "timeToRead": 4,
           "__typename": "Item"
         },
         "__typename": "Prospect"
@@ -1749,6 +1601,18 @@
           "code": "INVALID_GRAPHQL"
         }
       },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          4,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
       {
         "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
         "path": [
@@ -1761,6 +1625,18 @@
           "code": "INVALID_GRAPHQL"
         }
       },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          5,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
       {
         "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
         "path": [
@@ -1893,6 +1769,18 @@
           "code": "INVALID_GRAPHQL"
         }
       },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          11,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
       {
         "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
         "path": [
@@ -2397,6 +2285,18 @@
           "code": "INVALID_GRAPHQL"
         }
       },
+      {
+        "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          32,
+          "rejectedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
       {
         "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
         "path": [
@@ -2685,6 +2585,18 @@
           "code": "INVALID_GRAPHQL"
         }
       },
+      {
+        "message": "Cannot return null for non-nullable field ApprovedCorpusItem.externalId.",
+        "path": [
+          "getProspects",
+          45,
+          "approvedCorpusItem",
+          "externalId"
+        ],
+        "extensions": {
+          "code": "INVALID_GRAPHQL"
+        }
+      },
       {
         "message": "Cannot return null for non-nullable field RejectedCorpusItem.externalId.",
         "path": [
diff --git a/tests/unit/rankers/test_new_tab_scheduler.py b/tests/unit/rankers/test_new_tab_scheduler.py
index fec854fe6..0ab8a6edd 100644
--- a/tests/unit/rankers/test_new_tab_scheduler.py
+++ b/tests/unit/rankers/test_new_tab_scheduler.py
@@ -1,26 +1,40 @@
 import json
 import os
+from collections import Counter
 
-from pymoo.optimize import minimize
-from pymoo.algorithms.soo.nonconvex.ga import GA
+import pytest
 
 from app.config import ROOT_DIR
 from app.models.prospect_model import ProspectModel
-from app.rankers.new_tab_scheduler import ArticleSelectionProblem
+from app.rankers.new_tab_scheduler import select_articles, DEFAULT_DUPLICATE_LIMIT
 
 
-def test_new_tab_scheduler():
+@pytest.mark.parametrize('repeat', range(100))
+def test_new_tab_scheduler(repeat):
     with open(os.path.join(ROOT_DIR, 'tests/assets/json/get_prospects.json')) as fp:
         data = json.load(fp)
 
-    articles = [ProspectModel(**a) for a in data['data']['getProspects']]
+    article_data = data['data']['getProspects']
+    articles = [
+        ProspectModel(
+            quality_score=1 - (i / len(article_data)),  # dummy linear quality score based on ranking
+            **a
+        )
+        for i, a in enumerate(article_data)
+    ]
 
-    problem = ArticleSelectionProblem(articles)
+    selection = select_articles(articles)
 
-    algorithm = GA(pop_size=len(articles))  # JSON fixture has 50 articles
+    # Assert that close to the maximum number of articles are selected. 5000 iterations results in 17 selected articles.
+    assert len(selection) == pytest.approx(17, rel=1)
 
-    res = minimize(problem, algorithm, termination=('n_gen', 50))
+    # Assert that close to the maximum score achieved. 5000 iterations results in a sum of 12.6.
+    assert sum(a.quality_score for a in selection) == pytest.approx(12.6, rel=1)
 
-    # Decode the solution
-    selected_articles = [article for article, flag in zip(articles, res.X) if flag == 1]
-    print(selected_articles)
+    # The same topic can be selected at most twice.
+    for topic, count in Counter(a.topic for a in selection).items():
+        assert count <= DEFAULT_DUPLICATE_LIMIT, f"{count} {topic} items, which is more than {DEFAULT_DUPLICATE_LIMIT}"
+
+    # The same topic can be selected at most twice.
+    for pub, count in Counter(a.publisher for a in selection).items():
+        assert count <= DEFAULT_DUPLICATE_LIMIT, f"{count} {pub} items, which is more than {DEFAULT_DUPLICATE_LIMIT}"

From 890a4ba1d73a53a9dc71ab743a14aed61a17f23c Mon Sep 17 00:00:00 2001
From: Mathijs Miermans <m.miermans@gmail.com>
Date: Thu, 21 Dec 2023 14:58:37 -0800
Subject: [PATCH 3/6] feat: allow different limits on publishers and topics

---
 Pipfile                                      |  1 +
 Pipfile.lock                                 | 18 +++----
 app/rankers/new_tab_scheduler.py             | 36 ++++++++++---
 tests/unit/rankers/test_new_tab_scheduler.py | 56 +++++++++++++++-----
 4 files changed, 80 insertions(+), 31 deletions(-)

diff --git a/Pipfile b/Pipfile
index 7971528d8..88e05d46b 100644
--- a/Pipfile
+++ b/Pipfile
@@ -50,6 +50,7 @@ opentelemetry-exporter-otlp-proto-grpc = "*"
 opentelemetry-instrumentation-aiohttp-client = "==0.41b0"
 opentelemetry-instrumentation-fastapi = "==0.41b0"
 pymoo = "*"
+numpy = "*"
 
 [requires]
 python_version = "3.8"
diff --git a/Pipfile.lock b/Pipfile.lock
index ca55de9a7..c0c875c93 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "4c86364f8d3c3787cc44675ad28152129a1d96c9e515f48ade6910cae056b285"
+            "sha256": "4dc8a3a39d902a7ae5347b371db43c1316226268586743e550805368b3114ef3"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -1137,7 +1137,7 @@
                 "sha256:f136bab9c2cfd8da131132c2cf6cc27331dd6fae65f95f69dcd4ae3c3639c810",
                 "sha256:f3a86ed21e4f87050382c7bc96571755193c4c1392490744ac73d660e8f564a9"
             ],
-            "markers": "python_version >= '3.8'",
+            "index": "pypi",
             "version": "==1.24.4"
         },
         "opentelemetry-api": {
@@ -1815,11 +1815,11 @@
                 "standard"
             ],
             "hashes": [
-                "sha256:09c8e5a79dc466bdf28dead50093957db184de356fcdc48697bad3bde4c2588e",
-                "sha256:7c84fea70c619d4a710153482c0d230929af7bcf76c7bfa6de151f0a3a80121e"
+                "sha256:6dddbad1d7ee0f5140aba5ec138ddc9612c5109399903828b4874c9937f009c2",
+                "sha256:ce107f5d9bd02b4636001a77a4e74aab5e1e2b146868ebbad565237145af444c"
             ],
             "index": "pypi",
-            "version": "==0.24.0.post1"
+            "version": "==0.25.0"
         },
         "uvloop": {
             "hashes": [
@@ -2363,11 +2363,11 @@
         },
         "botocore-stubs": {
             "hashes": [
-                "sha256:c408265a12d97a467d58e0940d52323dda1faf4a02a07a4105d00e384a4e39c2",
-                "sha256:efa7e2e8ea9f4881b60703c7ddf5a4e64e66d6d03a20db046653235753b8d829"
+                "sha256:1d9c5fa2ec0015dc071f9f4225b062204f44e7193a0fb94b808bc11e4ee981d9",
+                "sha256:f7d578a5c27d64ea1ea6b75bf39c2c37f5c3ce77aed5dc06b5100ec2784d3d51"
             ],
-            "markers": "python_version >= '3.7' and python_version < '4.0'",
-            "version": "==1.34.4"
+            "markers": "python_version >= '3.8' and python_version < '4.0'",
+            "version": "==1.34.6"
         },
         "certifi": {
             "hashes": [
diff --git a/app/rankers/new_tab_scheduler.py b/app/rankers/new_tab_scheduler.py
index 895d0357f..a1932e00e 100644
--- a/app/rankers/new_tab_scheduler.py
+++ b/app/rankers/new_tab_scheduler.py
@@ -11,13 +11,15 @@
 from app.models.prospect_model import ProspectModel
 
 
-DEFAULT_DUPLICATE_LIMIT = 2
-
-
 class ArticleSelectionProblem(Problem):
-    def __init__(self, articles: List[ProspectModel], n_articles=30):
+    def __init__(
+            self,
+            articles: List[ProspectModel],
+            topic_duplicate_limit: int,
+            publisher_duplicate_limit: int
+    ):
         n_items = len(articles)
-        self.P = np.array([a.quality_score for a in articles])
+        self.P = np.array([a.quality_score for a in articles])  # profit
 
         all_topics = sorted({a.topic for a in articles})
         all_publishers = sorted({a.publisher for a in articles})
@@ -38,7 +40,9 @@ def __init__(self, articles: List[ProspectModel], n_articles=30):
         self.W = np.hstack((topic_matrix, publisher_matrix))
         n_constraints = self.W.shape[1]  # equal to len(all_topics) + len(all_publishers)
 
-        self.duplicate_limit = DEFAULT_DUPLICATE_LIMIT  # Maximum duplicate topics and publishers
+        # Create a vector for duplicate limits
+        self.duplicate_limit = np.array([topic_duplicate_limit] * len(all_topics) +
+                                        [publisher_duplicate_limit] * len(all_publishers))
 
         super().__init__(n_var=n_items, n_obj=1, n_ieq_constr=n_constraints, xl=0, xu=1, vtype=bool)
 
@@ -57,8 +61,24 @@ def __init__(self, articles):
             eliminate_duplicates=True)
 
 
-def select_articles(prospects: List[ProspectModel], n_gen=100) -> List[ProspectModel]:
-    problem = ArticleSelectionProblem(prospects)
+def select_articles(
+        prospects: List[ProspectModel],
+        topic_duplicate_limit: int = 2,
+        publisher_duplicate_limit: int = 2,
+        n_gen: int = 100,
+) -> List[ProspectModel]:
+    """
+    @param topic_duplicate_limit: Maximum number of items to select with the same topic
+    @param publisher_duplicate_limit: Maximum number of items to select with the same publisher
+    @param prospects: List of all available candidate items
+    @param n_gen: Number of generations
+    @return: a subset of prospects optimized for quality_score sum, with constraints on duplicate topics and publishers.
+    """
+    problem = ArticleSelectionProblem(
+        prospects,
+        topic_duplicate_limit=topic_duplicate_limit,
+        publisher_duplicate_limit=publisher_duplicate_limit,
+    )
     algorithm = ArticleSelectionAlgorithm(prospects)
     res = minimize(problem, algorithm, verbose=True, termination=('n_gen', n_gen))
     return [article for article, is_selected in zip(prospects, res.X) if is_selected]
diff --git a/tests/unit/rankers/test_new_tab_scheduler.py b/tests/unit/rankers/test_new_tab_scheduler.py
index 0ab8a6edd..ce3b88022 100644
--- a/tests/unit/rankers/test_new_tab_scheduler.py
+++ b/tests/unit/rankers/test_new_tab_scheduler.py
@@ -6,15 +6,38 @@
 
 from app.config import ROOT_DIR
 from app.models.prospect_model import ProspectModel
-from app.rankers.new_tab_scheduler import select_articles, DEFAULT_DUPLICATE_LIMIT
+from app.rankers.new_tab_scheduler import select_articles
 
 
-@pytest.mark.parametrize('repeat', range(100))
-def test_new_tab_scheduler(repeat):
+N_TEST_REPEATS = 10
+
+
+@pytest.fixture(scope="module")
+def prospects_data():
     with open(os.path.join(ROOT_DIR, 'tests/assets/json/get_prospects.json')) as fp:
-        data = json.load(fp)
+        return json.load(fp)
+
 
-    article_data = data['data']['getProspects']
+@pytest.mark.parametrize('repeat', range(N_TEST_REPEATS))
+@pytest.mark.parametrize(
+    'topic_duplicate_limit, publisher_duplicate_limit, optimal_length, optimal_total_score',
+    [
+        # Optimal length and total score were found by calling select_articles with n_gen=5000
+        (2, 2, 17, 12.6),
+        (1, 1, 10, 7.22),
+        (3, 2, 21, 14.2),
+        (0, 0, 0, 0),  # No prospects are expected to be selected when limits are 0
+        (50, 50, 50, 25.5),  # All prospects are expected to be selected when limits equal to the number of prospects
+    ])
+def test_new_tab_scheduler(
+        prospects_data,
+        repeat,
+        topic_duplicate_limit,
+        publisher_duplicate_limit,
+        optimal_length,
+        optimal_total_score,
+):
+    article_data = prospects_data['data']['getProspects']
     articles = [
         ProspectModel(
             quality_score=1 - (i / len(article_data)),  # dummy linear quality score based on ranking
@@ -23,18 +46,23 @@ def test_new_tab_scheduler(repeat):
         for i, a in enumerate(article_data)
     ]
 
-    selection = select_articles(articles)
+    selection = select_articles(
+        articles,
+        topic_duplicate_limit=topic_duplicate_limit,
+        publisher_duplicate_limit=publisher_duplicate_limit,
+        # n_gen=5000  # Uncomment to find what is presumed to be the optimal solution
+    )
 
-    # Assert that close to the maximum number of articles are selected. 5000 iterations results in 17 selected articles.
-    assert len(selection) == pytest.approx(17, rel=1)
+    # Check that the number of selected items is close to expected. abs=1 means that a difference of 1 is allowed.
+    assert len(selection) == pytest.approx(optimal_length, abs=1)
 
-    # Assert that close to the maximum score achieved. 5000 iterations results in a sum of 12.6.
-    assert sum(a.quality_score for a in selection) == pytest.approx(12.6, rel=1)
+    # Check that total score is close to expected. rel=.1 means that a difference of 10% is allowed.
+    assert sum(a.quality_score for a in selection) == pytest.approx(optimal_total_score, rel=.1)
 
-    # The same topic can be selected at most twice.
+    # Assert that the same topics are not selected too many times.
     for topic, count in Counter(a.topic for a in selection).items():
-        assert count <= DEFAULT_DUPLICATE_LIMIT, f"{count} {topic} items, which is more than {DEFAULT_DUPLICATE_LIMIT}"
+        assert count <= topic_duplicate_limit, f"{count} {topic} items is more than {topic_duplicate_limit}"
 
-    # The same topic can be selected at most twice.
+    # Assert that the same publishers are not selected too many times.
     for pub, count in Counter(a.publisher for a in selection).items():
-        assert count <= DEFAULT_DUPLICATE_LIMIT, f"{count} {pub} items, which is more than {DEFAULT_DUPLICATE_LIMIT}"
+        assert count <= publisher_duplicate_limit, f"{count} {pub} items is more than {publisher_duplicate_limit}"

From 8c5863ab065abb5747745e062dbc23b2785ffb58 Mon Sep 17 00:00:00 2001
From: Mathijs Miermans <m.miermans@gmail.com>
Date: Fri, 22 Dec 2023 10:51:59 -0800
Subject: [PATCH 4/6] feat: allow limits to be set by topic

---
 app/rankers/new_tab_scheduler.py             | 68 ++++++++++++++------
 tests/unit/rankers/test_new_tab_scheduler.py | 37 ++++++-----
 2 files changed, 70 insertions(+), 35 deletions(-)

diff --git a/app/rankers/new_tab_scheduler.py b/app/rankers/new_tab_scheduler.py
index a1932e00e..29922ca6a 100644
--- a/app/rankers/new_tab_scheduler.py
+++ b/app/rankers/new_tab_scheduler.py
@@ -1,11 +1,9 @@
-from typing import List
+from typing import List, Dict
 
 import numpy as np
-from pymoo.algorithms.soo.nonconvex.ga import GA
+from pymoo.algorithms.soo.nonconvex.ga import BGA
 from pymoo.core.problem import Problem
-from pymoo.operators.crossover.pntx import TwoPointCrossover
-from pymoo.operators.mutation.bitflip import BitflipMutation
-from pymoo.operators.sampling.rnd import BinaryRandomSampling
+from pymoo.operators.crossover.pntx import TwoPointCrossover, PointCrossover
 from pymoo.optimize import minimize
 
 from app.models.prospect_model import ProspectModel
@@ -15,7 +13,8 @@ class ArticleSelectionProblem(Problem):
     def __init__(
             self,
             articles: List[ProspectModel],
-            topic_duplicate_limit: int,
+            topic_duplicate_limits: Dict[str, int],
+            topic_duplicate_limit_fallback: int,
             publisher_duplicate_limit: int
     ):
         n_items = len(articles)
@@ -41,44 +40,73 @@ def __init__(
         n_constraints = self.W.shape[1]  # equal to len(all_topics) + len(all_publishers)
 
         # Create a vector for duplicate limits
-        self.duplicate_limit = np.array([topic_duplicate_limit] * len(all_topics) +
-                                        [publisher_duplicate_limit] * len(all_publishers))
+        self.duplicate_limit = np.array(
+            [topic_duplicate_limits.get(topic, topic_duplicate_limit_fallback) for topic in all_topics] +
+            [publisher_duplicate_limit] * len(all_publishers)
+        )
 
         super().__init__(n_var=n_items, n_obj=1, n_ieq_constr=n_constraints, xl=0, xu=1, vtype=bool)
 
     def _evaluate(self, x, out, *args, **kwargs):
+        """
+        @param x: Numpy array with shape (pop_size, n_var). This is a batch of potential solutions to be evaluated.
+        @param out["F"]: cost function values of shape (pop_size,)
+        @param out["G"]: constraint value array of shape (pop_size, n_constraints)
+        """
         out["F"] = -np.sum(self.P * x, axis=1)
         out["G"] = np.dot(x, self.W) - self.duplicate_limit
 
 
-class ArticleSelectionAlgorithm(GA):
-    def __init__(self, articles):
+class SchedulingGA(BGA):
+    def __init__(self):
         super().__init__(
-            pop_size=len(articles),
-            sampling=BinaryRandomSampling(),
-            crossover=TwoPointCrossover(),
-            mutation=BitflipMutation(),
-            eliminate_duplicates=True)
+            pop_size=50,
+            crossover=PointCrossover(n_points=2),
+        )
+
+
+DEFAULT_TOPIC_LIMITS = {
+    'ENTERTAINMENT': 5,
+    'FOOD': 5,
+    'SCIENCE': 4,
+    'HEALTH_FITNESS': 4,
+    'SELF_IMPROVEMENT': 4,
+    'EDUCATION': 3,
+    'POLITICS': 3,
+    'TECHNOLOGY': 2,
+    'PERSONAL_FINANCE': 2,
+    'BUSINESS': 2,
+    'CAREER': 2,
+    'TRAVEL': 2,
+    'PARENTING': 2,
+    'SPORTS': 1,
+}
 
 
 def select_articles(
         prospects: List[ProspectModel],
-        topic_duplicate_limit: int = 2,
+        topic_duplicate_limits=None,
+        topic_duplicate_limit_fallback: int = 2,
         publisher_duplicate_limit: int = 2,
         n_gen: int = 100,
 ) -> List[ProspectModel]:
     """
-    @param topic_duplicate_limit: Maximum number of items to select with the same topic
+    @param topic_duplicate_limits: Dictionary of maximum number of items with the same topics to select
+    @param topic_duplicate_limit_fallback: Fallback maximum number duplicate topics, for topics not present in the dict
     @param publisher_duplicate_limit: Maximum number of items to select with the same publisher
     @param prospects: List of all available candidate items
     @param n_gen: Number of generations
     @return: a subset of prospects optimized for quality_score sum, with constraints on duplicate topics and publishers.
     """
+    if topic_duplicate_limits is None:
+        topic_duplicate_limits = DEFAULT_TOPIC_LIMITS
+
     problem = ArticleSelectionProblem(
         prospects,
-        topic_duplicate_limit=topic_duplicate_limit,
+        topic_duplicate_limits=topic_duplicate_limits,
+        topic_duplicate_limit_fallback=topic_duplicate_limit_fallback,
         publisher_duplicate_limit=publisher_duplicate_limit,
     )
-    algorithm = ArticleSelectionAlgorithm(prospects)
+    algorithm = SchedulingGA()
     res = minimize(problem, algorithm, verbose=True, termination=('n_gen', n_gen))
-    return [article for article, is_selected in zip(prospects, res.X) if is_selected]
+    return [article for article, x in zip(prospects, res.X) if float(x) > 0.5]
diff --git a/tests/unit/rankers/test_new_tab_scheduler.py b/tests/unit/rankers/test_new_tab_scheduler.py
index ce3b88022..57b117335 100644
--- a/tests/unit/rankers/test_new_tab_scheduler.py
+++ b/tests/unit/rankers/test_new_tab_scheduler.py
@@ -6,8 +6,7 @@
 
 from app.config import ROOT_DIR
 from app.models.prospect_model import ProspectModel
-from app.rankers.new_tab_scheduler import select_articles
-
+from app.rankers.new_tab_scheduler import select_articles, DEFAULT_TOPIC_LIMITS
 
 N_TEST_REPEATS = 10
 
@@ -20,19 +19,25 @@ def prospects_data():
 
 @pytest.mark.parametrize('repeat', range(N_TEST_REPEATS))
 @pytest.mark.parametrize(
-    'topic_duplicate_limit, publisher_duplicate_limit, optimal_length, optimal_total_score',
+    'topic_duplicate_limits,'
+    'topic_duplicate_limit_fallback,'
+    'publisher_duplicate_limit,'
+    'optimal_length,'
+    'optimal_total_score',
     [
         # Optimal length and total score were found by calling select_articles with n_gen=5000
-        (2, 2, 17, 12.6),
-        (1, 1, 10, 7.22),
-        (3, 2, 21, 14.2),
-        (0, 0, 0, 0),  # No prospects are expected to be selected when limits are 0
-        (50, 50, 50, 25.5),  # All prospects are expected to be selected when limits equal to the number of prospects
+        (dict(), 2, 2, 17, 12.6),
+        (dict(), 1, 1, 10, 7.22),
+        (dict(), 3, 2, 21, 14.2),
+        (dict(), 0, 0, 0, 0),  # No prospects are expected to be selected when limits are 0
+        (dict(), 50, 50, 50, 25.5),  # All prospects are selected when limits are high
+        (DEFAULT_TOPIC_LIMITS, 2, 2, 21, 13.94),  # Default topic limits
     ])
 def test_new_tab_scheduler(
         prospects_data,
         repeat,
-        topic_duplicate_limit,
+        topic_duplicate_limits,
+        topic_duplicate_limit_fallback,
         publisher_duplicate_limit,
         optimal_length,
         optimal_total_score,
@@ -48,20 +53,22 @@ def test_new_tab_scheduler(
 
     selection = select_articles(
         articles,
-        topic_duplicate_limit=topic_duplicate_limit,
+        topic_duplicate_limits=topic_duplicate_limits,
+        topic_duplicate_limit_fallback=topic_duplicate_limit_fallback,
         publisher_duplicate_limit=publisher_duplicate_limit,
         # n_gen=5000  # Uncomment to find what is presumed to be the optimal solution
     )
 
-    # Check that the number of selected items is close to expected. abs=1 means that a difference of 1 is allowed.
-    assert len(selection) == pytest.approx(optimal_length, abs=1)
+    # Check that the number of selected items is close to expected. abs=2 means that a difference of 2 is allowed.
+    assert len(selection) == pytest.approx(optimal_length, abs=2)
 
-    # Check that total score is close to expected. rel=.1 means that a difference of 10% is allowed.
-    assert sum(a.quality_score for a in selection) == pytest.approx(optimal_total_score, rel=.1)
+    # Check that total score is close to expected. rel=.2 means that a difference of 20% is allowed.
+    assert sum(a.quality_score for a in selection) == pytest.approx(optimal_total_score, rel=.2)
 
     # Assert that the same topics are not selected too many times.
     for topic, count in Counter(a.topic for a in selection).items():
-        assert count <= topic_duplicate_limit, f"{count} {topic} items is more than {topic_duplicate_limit}"
+        assert count <= topic_duplicate_limits.get(topic, topic_duplicate_limit_fallback),\
+            f"{count} {topic} items is more than {topic_duplicate_limit_fallback}"
 
     # Assert that the same publishers are not selected too many times.
     for pub, count in Counter(a.publisher for a in selection).items():

From 487360c7d4d1a241c78e95a80287764fc4ac0951 Mon Sep 17 00:00:00 2001
From: Mathijs Miermans <m.miermans@gmail.com>
Date: Fri, 22 Dec 2023 10:55:05 -0800
Subject: [PATCH 5/6] chore: add comment on topic counts

---
 app/rankers/new_tab_scheduler.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/app/rankers/new_tab_scheduler.py b/app/rankers/new_tab_scheduler.py
index 29922ca6a..e961c2408 100644
--- a/app/rankers/new_tab_scheduler.py
+++ b/app/rankers/new_tab_scheduler.py
@@ -65,6 +65,9 @@ def __init__(self):
         )
 
 
+"""
+Values below are the 75th percentile topic counts per day, scheduled on NEW_TAB_EN_US between 2023-06-01 and 2023-12-22.
+"""
 DEFAULT_TOPIC_LIMITS = {
     'ENTERTAINMENT': 5,
     'FOOD': 5,

From e61d7420ed9fb8da2c5d86460e4cedd36b03dd21 Mon Sep 17 00:00:00 2001
From: Mathijs Miermans <m.miermans@gmail.com>
Date: Fri, 22 Dec 2023 11:12:33 -0800
Subject: [PATCH 6/6] chore: cleanup test

---
 app/rankers/new_tab_scheduler.py             |  4 +--
 tests/unit/rankers/test_new_tab_scheduler.py | 32 +++++++++++---------
 2 files changed, 19 insertions(+), 17 deletions(-)

diff --git a/app/rankers/new_tab_scheduler.py b/app/rankers/new_tab_scheduler.py
index e961c2408..1e710ab31 100644
--- a/app/rankers/new_tab_scheduler.py
+++ b/app/rankers/new_tab_scheduler.py
@@ -3,7 +3,7 @@
 import numpy as np
 from pymoo.algorithms.soo.nonconvex.ga import BGA
 from pymoo.core.problem import Problem
-from pymoo.operators.crossover.pntx import TwoPointCrossover, PointCrossover
+from pymoo.operators.crossover.pntx import PointCrossover
 from pymoo.optimize import minimize
 
 from app.models.prospect_model import ProspectModel
@@ -111,5 +111,5 @@ def select_articles(
         publisher_duplicate_limit=publisher_duplicate_limit,
     )
     algorithm = SchedulingGA()
-    res = minimize(problem, algorithm, verbose=True, termination=('n_gen', n_gen))
+    res = minimize(problem, algorithm, termination=('n_gen', n_gen))
     return [article for article, x in zip(prospects, res.X) if float(x) > 0.5]
diff --git a/tests/unit/rankers/test_new_tab_scheduler.py b/tests/unit/rankers/test_new_tab_scheduler.py
index 57b117335..c718dbc96 100644
--- a/tests/unit/rankers/test_new_tab_scheduler.py
+++ b/tests/unit/rankers/test_new_tab_scheduler.py
@@ -17,6 +17,18 @@ def prospects_data():
         return json.load(fp)
 
 
+@pytest.fixture()
+def prospects(prospects_data):
+    prospects_list = prospects_data['data']['getProspects']
+    return [
+        ProspectModel(
+            quality_score=1 - (i / len(prospects_list)),  # dummy linear quality score based on ranking
+            **a
+        )
+        for i, a in enumerate(prospects_list)
+    ]
+
+
 @pytest.mark.parametrize('repeat', range(N_TEST_REPEATS))
 @pytest.mark.parametrize(
     'topic_duplicate_limits,'
@@ -26,15 +38,14 @@ def prospects_data():
     'optimal_total_score',
     [
         # Optimal length and total score were found by calling select_articles with n_gen=5000
-        (dict(), 2, 2, 17, 12.6),
-        (dict(), 1, 1, 10, 7.22),
-        (dict(), 3, 2, 21, 14.2),
+        (DEFAULT_TOPIC_LIMITS, 2, 2, 21, 13.94),  # Different limits per topic
+        (dict(), 3, 2, 21, 14.2),  # Fixed topic (3) and publisher (2) limits
+        (dict(), 1, 1, 10, 7.22),  # Fixed topic (1) and publisher (1) limits
         (dict(), 0, 0, 0, 0),  # No prospects are expected to be selected when limits are 0
         (dict(), 50, 50, 50, 25.5),  # All prospects are selected when limits are high
-        (DEFAULT_TOPIC_LIMITS, 2, 2, 21, 13.94),  # Default topic limits
     ])
 def test_new_tab_scheduler(
-        prospects_data,
+        prospects,
         repeat,
         topic_duplicate_limits,
         topic_duplicate_limit_fallback,
@@ -42,17 +53,8 @@ def test_new_tab_scheduler(
         optimal_length,
         optimal_total_score,
 ):
-    article_data = prospects_data['data']['getProspects']
-    articles = [
-        ProspectModel(
-            quality_score=1 - (i / len(article_data)),  # dummy linear quality score based on ranking
-            **a
-        )
-        for i, a in enumerate(article_data)
-    ]
-
     selection = select_articles(
-        articles,
+        prospects,
         topic_duplicate_limits=topic_duplicate_limits,
         topic_duplicate_limit_fallback=topic_duplicate_limit_fallback,
         publisher_duplicate_limit=publisher_duplicate_limit,