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

examples/load_dataframe.py

@@ -0,0 +1,66 @@
+"""
+Load ActivityWatch data into a dataframe, and export as CSV.
+"""
+
+import os
+import socket
+from datetime import datetime, timedelta, timezone
+
+import iso8601
+import pandas as pd
+from aw_client import ActivityWatchClient
+from aw_client.classes import default_classes
+from aw_client.queries import DesktopQueryParams, canonicalEvents
+
+
+def build_query() -> str:
+    hostname = "fakedata" if os.getenv("CI") else socket.gethostname()
+    canonicalQuery = canonicalEvents(
+        DesktopQueryParams(
+            bid_window=f"aw-watcher-window_{hostname}",
+            bid_afk=f"aw-watcher-afk_{hostname}",
+            classes=default_classes,
+        )
+    )
+    return f"""
+    {canonicalQuery}
+    RETURN = {{"events": events}};
+    """
+
+
+def main() -> None:
+    now = datetime.now(tz=timezone.utc)
+    td30d = timedelta(days=30)
+
+    aw = ActivityWatchClient()
+    print("Querying...")
+    query = build_query()
+    data = aw.query(query, [(now - td30d, now)])
+
+    events = [
+        {
+            "timestamp": e["timestamp"],
+            "duration": timedelta(seconds=e["duration"]),
+            **e["data"],
+        }
+        for e in data[0]["events"]
+    ]
+
+    for e in events:
+        e["$category"] = " > ".join(e["$category"])
+
+    df = pd.json_normalize(events)
+    df["timestamp"] = pd.to_datetime(df["timestamp"].apply(iso8601.parse_date))
+    df.set_index("timestamp", inplace=True)
+
+    print(df)
+
+    answer = input("Do you want to export to CSV? (y/N): ")
+    if answer == "y":
+        filename = "output.csv"
+        df.to_csv(filename)
+        print(f"Wrote to {filename}")
+
+
+if __name__ == "__main__":
+    main()