update

takway/apps/data_struct.py

@@ -0,0 +1,133 @@
+import multiprocessing
+import queue
+from typing import Iterator
+import time
+import json
+import requests
+
+class QueueIterator:
+    def __init__(self, 
+                 queue, 
+                 timeout: int = 10):
+        self.queue = queue
+        self.timeout = timeout
+
+    def __iter__(self) -> Iterator:
+        return self
+
+    def __next__(self):
+        try:
+            data = self.queue.get(block=True, timeout=self.timeout)
+            if data is None:  # 使用None作为结束信号
+                # print("QueueIterator: End of data")
+                raise StopIteration
+            else:
+                # print("QueueIterator: Get data")
+                return data
+        except queue.Empty:
+            # print("QueueIterator: Queue is empty")
+            raise StopIteration
+
+
+
+
+def producer(queue: multiprocessing.Queue):
+    for i in range(5):  # 假设生产5个数据项
+        data = {'data': i, 'is_end': False}
+        queue.put(data)
+        time.sleep(1)
+    queue.put(None)  # 发送结束信号
+
+def get_stream_data_from_queue(queue: multiprocessing.Queue):
+    for data in QueueIterator(queue):
+        print(data)
+        yield json.dumps({'line': data, 'is_end': False})
+        # 模拟数据处理时间
+
+if __name__ == "__main__":
+    queue = multiprocessing.Queue()
+    # 创建并启动生产者进程
+    p = multiprocessing.Process(target=producer, args=(queue,))
+    p.start()
+
+    # 使用迭代器来消费Queue中的数据
+    for data in QueueIterator(queue):
+        print(data)
+
+    # 等待生产者进程结束
+    p.join()
+
+
+'''
+# request body
+{
+    "AUTH_INFO": {
+        "user": "", # string
+        "authid": "",   # string
+        "api_keys": "",  # string
+        "timestamp": "",  # string
+    },
+    "DATA": {
+        "Audio": {
+            "data": "xxxxx",    # base64 encoded data
+            "metadata": {
+                "rate": ;   # int
+                "channels": ;   # int
+                "format": ;  # int
+            }
+        },
+        "Text": {
+            "data": "xxxxx",    # base64 encoded data
+            "metadata": {
+                # TODO
+            }
+        },
+        "Image": {
+            "data": "xxxxx",    # base64 encoded data
+            "metadata": {
+                "width": ;  # int
+                "height": ; # int
+                "format": ; # string
+            }
+        }
+    }
+    "META_INFO": {
+        "model_type": "",     # string
+        "model_version": "",    # string
+        "model_url": "",    # string
+        "vits": {
+            "speaker_id": ;  # int
+    }
+}
+
+# response body
+{
+    RESPONSE_INFO: {
+        "status": "success/error",   # string
+        "message": "xxxxx",  # string
+    }
+    "DATA": {
+        "Audio": {
+            "data": "xxxxx",    # base64 encoded data
+            "metadata": {
+                "rate": ;   # int
+                "channels": ;   # int
+                "format": ;  # int
+            }
+        },
+        "Text": {
+            "data": "xxxxx",    # base64 encoded data
+            "metadata": {
+                "is_end": True/False,  # bool
+            }
+        }
+        "Image": {
+            "data": "xxxxx",    # base64 encoded data
+            "metadata": {
+                "width": ;  # int
+                "height": ; # int
+                "format": ; # string
+            }
+        }
+}
+'''