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authormia <mia@mia.jetzt>2024-09-04 04:47:13 -0700
committermia <mia@mia.jetzt>2024-09-04 04:47:13 -0700
commitbb8a48fd4d85ba4f8224c68aaaf9069d5d79dae2 (patch)
treebdb0654c667f37c69addc9efd1e29b9cfe710c51 /conf_mia.py
parent81071e8feefdf815e29318226c668664e1706da2 (diff)
downloadscrubber-bb8a48fd4d85ba4f8224c68aaaf9069d5d79dae2.tar.gz
scrubber-bb8a48fd4d85ba4f8224c68aaaf9069d5d79dae2.zip
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+import math
+from datetime import UTC, datetime, timedelta
+
+from com import FilterableNote, Visibility
+from sec import connect, tokens
+
+user_id = "9gf2ev4ex5dflllo"
+token = tokens["mia"]
+api = "https://void.rehab/api/"
+early_exit = 0xFFF
+
+now = datetime.now(UTC)
+threshold = 0.1
+
+def criteria(root: FilterableNote) -> bool:
+    thread = root.thread()
+    thread_self = root.thread_self()
+
+    # if there are dms involved...
+    low_vis = min(thread, key=lambda note: note.visibility.value)
+    if low_vis.visibility == Visibility.direct:
+        is_direct = lambda note: note.visibility == Visibility.direct
+        most_recent_direct = max(filter(is_direct, thread), key=lambda note: note.when)
+        # ...and the dms are younger than two months...
+        if now - most_recent_direct.when < timedelta(days=30 * 2):
+            # ...do not delete the thread
+            return False
+
+    # get the most recent post...
+    others_recency = max(thread, key=lambda note: note.when)
+    # ...and bail if it's too new
+    if now - others_recency.when < timedelta(days=14):
+        return False
+
+    # get my...
+    most_recent_post = max(thread_self, key=lambda note: note.when) # ...most recent post...
+    score = lambda note: note.reactions + note.renotes*5
+    high_score_post = max(thread_self, key=score) # ...highest scoring post...
+    # ...and their values...
+    most_recent = most_recent_post.when
+    most_recent_age = now - most_recent
+    high_score = score(high_score_post)
+    # ...weigh it...
+    weighted_score = high_score / math.sqrt(most_recent_age.days)
+    # ...and check it against a threshold
+    return weighted_score < threshold