snapshot of https://github.com/ActivityWatch/aw-client.git (master, 2026-09-16; blobs > 131072B omitted)

examples/suggest_categories.py

@@ -0,0 +1,88 @@
+"""
+Lists the most common words among uncategorized events, by duration, to help in creating categories.
+
+This might make more sense as a notebook.
+"""
+
+from collections import Counter
+from datetime import datetime, timedelta, timezone
+from tabulate import tabulate
+from typing import Dict, List, Tuple, Any
+
+from aw_core import Event
+import aw_client
+from aw_client import queries
+
+# set up client
+awc = aw_client.ActivityWatchClient("test")
+
+
+def example_categories():
+    # TODO: Use tools in aw-research to load categories from toml file
+    return [
+        (
+            ("Work", "ActivityWatch"),
+            {"type": "regex", "regex": "aw-|activitywatch", "ignore_case": True},
+        ),
+    ]
+
+
+def get_events(categories=List[Tuple[Tuple[str], Dict[str, Any]]]):
+    """
+    Retrieves AFK-filtered events, only returns events which are Uncategorized.
+    """
+
+    start = datetime(2022, 1, 1, tzinfo=timezone.utc)
+    now = datetime.now(tz=timezone.utc)
+    timeperiods = [(start, now)]
+
+    canonicalQuery = queries.canonicalEvents(
+        queries.DesktopQueryParams(
+            bid_window="aw-watcher-window_",
+            bid_afk="aw-watcher-afk_",
+            classes=categories,
+        )
+    )
+    res = awc.query(
+        f"""
+        {canonicalQuery}
+        events = filter_keyvals(events, "$category", [["Uncategorized"]]);
+        duration = sum_durations(events);
+        RETURN = {{"events": events, "duration": duration}};
+        """,
+        timeperiods,
+    )
+    events = res[0]["events"]
+    print(f"Fetched {len(events)} events")
+    return [Event(**e) for e in events]
+
+
+def events2words(events):
+    for e in events:
+        for v in e.data.values():
+            if isinstance(v, str):
+                for word in v.split():
+                    if len(word) >= 3:
+                        # normalize
+                        word = word.lower()
+                        yield (word, e.duration)
+
+
+def main():
+    categories = example_categories()
+    events = get_events(categories)
+
+    # find most common words, by duration
+    corpus: Dict[str, timedelta] = Counter()  # type: ignore
+    for word, duration in events2words(events):
+        if word not in corpus:
+            corpus[word] = timedelta(0)
+        corpus[word] += duration
+
+    # The top words are rarely useful for categorization, as they are usually browsers and other categories
+    # of activity which are too broad for it to make sense as a rule (except as a fallback).
+    print(tabulate(corpus.most_common(50), headers=["word", "duration"]))  # type: ignore
+
+
+if __name__ == "__main__":
+    main()