feat: optipng worker

optimizer_worker.py

@@ -0,0 +1,57 @@
+from tempfile import TemporaryDirectory
+import json
+import time
+import logging
+
+from src.git import clone_repo
+from src.optipng import apply_optipng_recursive
+from src.messages import AnalyzeTask, AnalyzeResponse, create_analyze_response
+from src.rabbit import get_channel, send_reply
+from src.settings import RABBIT_TASK_QUEUE, init_logging, WORKER_NAME
+
+
+def process_task(task: AnalyzeTask) -> AnalyzeResponse:
+    with TemporaryDirectory() as repo_path:
+        clone_begin_at = time.monotonic()
+        clone_repo(task.url, repo_path)
+        clone_duration = time.monotonic() - clone_begin_at
+        base_size, after_size = apply_optipng_recursive(repo_path, level=task.level)
+        optipng_duration = time.monotonic() - clone_begin_at - clone_duration
+        return create_analyze_response(
+            task,
+            base_size,
+            after_size,
+            clone_duration=clone_duration,
+            duration=optipng_duration,
+            worker=WORKER_NAME,
+        )
+
+
+def rabbit_callback(ch, method, properties, body):
+    task = AnalyzeTask.from_data(json.loads(body))
+    logging.info(f"New task url: {task.url}, level: {task.level}")
+    try:
+        res = process_task(task).data
+        res["status"] = "success"
+    except Exception as err:
+        logging.exception(f"Error {err} with {task.url}")
+        res = {
+            "status": "error",
+            "message": str(err),
+            "task_id": task.task_id
+        }
+    send_reply(ch, json.dumps(res).encode("utf-8"))
+
+
+def main():
+    channel = get_channel()
+
+    channel.basic_consume(
+        queue=RABBIT_TASK_QUEUE, on_message_callback=rabbit_callback, auto_ack=True
+    )
+    channel.start_consuming()
+
+
+if __name__ == "__main__":
+    init_logging()
+    main()