{"id":1151646,"date":"2025-01-13T17:16:06","date_gmt":"2025-01-13T09:16:06","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1151646.html"},"modified":"2025-01-13T17:16:08","modified_gmt":"2025-01-13T09:16:08","slug":"python%e5%a6%82%e4%bd%95%e5%8f%91%e6%8c%a5%e5%a4%9a%e6%a0%b8%e6%80%a7%e8%83%bd","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1151646.html","title":{"rendered":"python\u5982\u4f55\u53d1\u6325\u591a\u6838\u6027\u80fd"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25181833\/e54d4c46-f598-45bf-b369-7987b099ba13.webp\" alt=\"python\u5982\u4f55\u53d1\u6325\u591a\u6838\u6027\u80fd\" \/><\/p>\n<p><p> <strong>Python\u53d1\u6325\u591a\u6838\u6027\u80fd\u7684\u65b9\u6cd5\u6709\u591a\u7ebf\u7a0b\u3001\u591a\u8fdb\u7a0b\u3001\u5e76\u884c\u8ba1\u7b97\u5e93\u3001\u5f02\u6b65\u7f16\u7a0b<\/strong>\u3002\u5176\u4e2d\uff0c<strong>\u591a\u8fdb\u7a0b<\/strong>\u662f\u4e00\u79cd\u975e\u5e38\u6709\u6548\u7684\u65b9\u6cd5\u3002Python\u4e2d\u7684\u5168\u5c40\u89e3\u91ca\u5668\u9501\uff08GIL\uff09\u9650\u5236\u4e86\u591a\u7ebf\u7a0b\u7684\u5e76\u884c\u6267\u884c\uff0c\u800c\u591a\u8fdb\u7a0b\u53ef\u4ee5\u5145\u5206\u5229\u7528\u591a\u6838CPU\u7684\u4f18\u52bf\u3002\u901a\u8fc7\u4f7f\u7528\u591a\u8fdb\u7a0b\u5e93\uff08\u5982<code>multiprocessing<\/code>\uff09\uff0c\u53ef\u4ee5\u521b\u5efa\u591a\u4e2a\u72ec\u7acb\u7684\u8fdb\u7a0b\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u8fd0\u884c\u5728\u4e0d\u540c\u7684CPU\u6838\u5fc3\u4e0a\uff0c\u4ece\u800c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u591a\u7ebf\u7a0b\u4e0eGIL<\/h3>\n<\/p>\n<p><p><strong>\u591a\u7ebf\u7a0b<\/strong>\u662f\u6307\u5728\u4e00\u4e2a\u8fdb\u7a0b\u5185\u521b\u5efa\u591a\u4e2a\u7ebf\u7a0b\uff0c\u6bcf\u4e2a\u7ebf\u7a0b\u53ef\u4ee5\u72ec\u7acb\u6267\u884c\u4ee3\u7801\u3002\u7136\u800c\uff0c\u7531\u4e8ePython\u4e2d\u7684GIL\uff08\u5168\u5c40\u89e3\u91ca\u5668\u9501\uff09\uff0c\u5728CPython\u89e3\u91ca\u5668\u4e2d\uff0c\u53ea\u6709\u4e00\u4e2a\u7ebf\u7a0b\u80fd\u591f\u6267\u884cPython\u5b57\u8282\u7801\u3002GIL\u7684\u5b58\u5728\u4f7f\u5f97\u591a\u7ebf\u7a0b\u5728\u591a\u6838CPU\u4e0a\u5e76\u4e0d\u80fd\u771f\u6b63\u5e76\u884c\u6267\u884c\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>GIL\u7684\u5f71\u54cd<\/strong>\uff1aGIL\u4f1a\u5bfc\u81f4\u591a\u7ebf\u7a0b\u5728\u8ba1\u7b97\u5bc6\u96c6\u578b\u4efb\u52a1\u4e2d\u4e0d\u80fd\u5145\u5206\u5229\u7528\u591a\u6838CPU\u7684\u4f18\u52bf\uff0c\u56e0\u4e3a\u53ea\u6709\u4e00\u4e2a\u7ebf\u7a0b\u80fd\u591f\u6267\u884cPython\u4ee3\u7801\uff0c\u5176\u5b83\u7ebf\u7a0b\u5904\u4e8e\u7b49\u5f85\u72b6\u6001\u3002\u8fd9\u4f7f\u5f97\u591a\u7ebf\u7a0b\u5728I\/O\u5bc6\u96c6\u578b\u4efb\u52a1\u4e2d\u8868\u73b0\u8f83\u597d\uff0c\u800c\u5728CPU\u5bc6\u96c6\u578b\u4efb\u52a1\u4e2d\u8868\u73b0\u4e0d\u4f73\u3002<\/li>\n<li><strong>\u9002\u7528\u573a\u666f<\/strong>\uff1a\u591a\u7ebf\u7a0b\u4e3b\u8981\u9002\u7528\u4e8eI\/O\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u5982\u6587\u4ef6\u8bfb\u5199\u3001\u7f51\u7edc\u8bf7\u6c42\u7b49\u3002\u5728\u8fd9\u4e9b\u4efb\u52a1\u4e2d\uff0c\u7ebf\u7a0b\u53ef\u4ee5\u5728\u7b49\u5f85I\/O\u64cd\u4f5c\u5b8c\u6210\u65f6\u6267\u884c\u5176\u5b83\u4efb\u52a1\uff0c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u54cd\u5e94\u901f\u5ea6\u548c\u5e76\u53d1\u80fd\u529b\u3002<\/li>\n<\/ul>\n<p><h3>\u4e8c\u3001\u591a\u8fdb\u7a0b<\/h3>\n<\/p>\n<p><p><strong>\u591a\u8fdb\u7a0b<\/strong>\u662f\u6307\u5728\u4e00\u4e2a\u7a0b\u5e8f\u5185\u521b\u5efa\u591a\u4e2a\u72ec\u7acb\u7684\u8fdb\u7a0b\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u6709\u81ea\u5df1\u7684\u5185\u5b58\u7a7a\u95f4\u548cGIL\u3002\u8fd9\u6837\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u90fd\u53ef\u4ee5\u5728\u4e0d\u540c\u7684CPU\u6838\u5fc3\u4e0a\u72ec\u7acb\u8fd0\u884c\uff0c\u4ece\u800c\u5b9e\u73b0\u771f\u6b63\u7684\u5e76\u884c\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>multiprocessing\u5e93<\/strong>\uff1aPython\u7684<code>multiprocessing<\/code>\u5e93\u63d0\u4f9b\u4e86\u7b80\u5355\u6613\u7528\u7684\u63a5\u53e3\u6765\u521b\u5efa\u548c\u7ba1\u7406\u8fdb\u7a0b\u3002\u901a\u8fc7<code>multiprocessing.Pool<\/code>\u7c7b\u53ef\u4ee5\u65b9\u4fbf\u5730\u521b\u5efa\u4e00\u4e2a\u8fdb\u7a0b\u6c60\uff0c\u5e76\u5c06\u4efb\u52a1\u5206\u914d\u7ed9\u591a\u4e2a\u8fdb\u7a0b\u6267\u884c\u3002<\/li>\n<li><strong>\u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a\n<pre><code class=\"language-python\">import multiprocessing<\/p>\n<p>import os<\/p>\n<p>def worker(num):<\/p>\n<p>    print(f&#39;Worker: {num}, PID: {os.getpid()}&#39;)<\/p>\n<p>if __name__ == &#39;__m<a href=\"https:\/\/docs.pingcode.com\/blog\/59162.html\" target=\"_blank\">AI<\/a>n__&#39;:<\/p>\n<p>    processes = []<\/p>\n<p>    for i in range(5):<\/p>\n<p>        p = multiprocessing.Process(target=worker, args=(i,))<\/p>\n<p>        processes.append(p)<\/p>\n<p>        p.start()<\/p>\n<p>    for p in processes:<\/p>\n<p>        p.join()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u521b\u5efa\u4e865\u4e2a\u8fdb\u7a0b\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u6267\u884c<code>worker<\/code>\u51fd\u6570\u3002\u6bcf\u4e2a\u8fdb\u7a0b\u90fd\u6709\u72ec\u7acb\u7684PID\uff0c\u53ef\u4ee5\u5728\u4e0d\u540c\u7684CPU\u6838\u5fc3\u4e0a\u8fd0\u884c\u3002<\/li>\n<\/p>\n<\/ul>\n<p><h3>\u4e09\u3001\u5e76\u884c\u8ba1\u7b97\u5e93<\/h3>\n<\/p>\n<p><p>Python\u4e2d\u6709\u8bb8\u591a\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u53ef\u4ee5\u5e2e\u52a9\u5f00\u53d1\u8005\u5145\u5206\u5229\u7528\u591a\u6838CPU\u7684\u6027\u80fd\u3002\u8fd9\u4e9b\u5e93\u901a\u5e38\u63d0\u4f9b\u4e86\u9ad8\u5c42\u6b21\u7684\u63a5\u53e3\uff0c\u7b80\u5316\u4e86\u5e76\u884c\u8ba1\u7b97\u7684\u5b9e\u73b0\u8fc7\u7a0b\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>NumPy<\/strong>\uff1aNumPy\u662f\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u5e93\uff0c\u652f\u6301\u591a\u7ef4\u6570\u7ec4\u548c\u77e9\u9635\u8fd0\u7b97\u3002\u901a\u8fc7NumPy\u7684\u5e7f\u64ad\u673a\u5236\u548c\u5411\u91cf\u5316\u64cd\u4f5c\uff0c\u53ef\u4ee5\u5229\u7528\u5e95\u5c42\u7684C\u548cFortran\u4ee3\u7801\u8fdb\u884c\u9ad8\u6548\u7684\u5e76\u884c\u8ba1\u7b97\u3002<\/li>\n<li><strong>Dask<\/strong>\uff1aDask\u662f\u4e00\u4e2a\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u652f\u6301\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u548c\u8ba1\u7b97\u3002Dask\u53ef\u4ee5\u5c06\u5927\u6570\u636e\u96c6\u5206\u5272\u6210\u591a\u4e2a\u5c0f\u5757\uff0c\u5e76\u5728\u591a\u4e2a\u8fdb\u7a0b\u6216\u7ebf\u7a0b\u4e0a\u5e76\u884c\u5904\u7406\u3002<\/li>\n<li><strong>\u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a\n<pre><code class=\"language-python\">import dask.array as da<\/p>\n<h2><strong>\u521b\u5efa\u4e00\u4e2aDask\u6570\u7ec4<\/strong><\/h2>\n<p>x = da.random.random((10000, 10000), chunks=(1000, 1000))<\/p>\n<p>y = x + x.T<\/p>\n<h2><strong>\u8ba1\u7b97\u7ed3\u679c<\/strong><\/h2>\n<p>result = y.compute()<\/p>\n<p>print(result)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u521b\u5efa\u4e86\u4e00\u4e2a\u968f\u673a\u6570\u7ec4\uff0c\u5e76\u8fdb\u884c\u4e86\u77e9\u9635\u52a0\u6cd5\u8fd0\u7b97\u3002Dask\u4f1a\u81ea\u52a8\u5c06\u8ba1\u7b97\u4efb\u52a1\u5206\u914d\u7ed9\u591a\u4e2a\u8fdb\u7a0b\u8fdb\u884c\u5e76\u884c\u5904\u7406\u3002<\/li>\n<\/p>\n<\/ul>\n<p><h3>\u56db\u3001\u5f02\u6b65\u7f16\u7a0b<\/h3>\n<\/p>\n<p><p><strong>\u5f02\u6b65\u7f16\u7a0b<\/strong>\u662f\u4e00\u79cd\u5904\u7406\u5e76\u53d1\u4efb\u52a1\u7684\u65b9\u6cd5\uff0c\u901a\u8fc7\u5f02\u6b65I\/O\u64cd\u4f5c\u548c\u4e8b\u4ef6\u5faa\u73af\u5b9e\u73b0\u9ad8\u6548\u7684\u5e76\u53d1\u6267\u884c\u3002Python\u4e2d\u7684<code>asyncio<\/code>\u5e93\u63d0\u4f9b\u4e86\u5f02\u6b65\u7f16\u7a0b\u7684\u652f\u6301\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>asyncio\u5e93<\/strong>\uff1a<code>asyncio<\/code>\u5e93\u63d0\u4f9b\u4e86\u4e8b\u4ef6\u5faa\u73af\u3001\u534f\u7a0b\u548c\u4efb\u52a1\u7b49\u5f02\u6b65\u7f16\u7a0b\u7684\u57fa\u672c\u6784\u4ef6\u3002\u901a\u8fc7<code>async<\/code>\u548c<code>await<\/code>\u5173\u952e\u5b57\uff0c\u53ef\u4ee5\u5b9a\u4e49\u548c\u8c03\u7528\u5f02\u6b65\u51fd\u6570\u3002<\/li>\n<li><strong>\u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a\n<pre><code class=\"language-python\">import asyncio<\/p>\n<p>async def worker(num):<\/p>\n<p>    print(f&#39;Worker: {num}&#39;)<\/p>\n<p>    await asyncio.sleep(1)<\/p>\n<p>    print(f&#39;Worker: {num} done&#39;)<\/p>\n<p>async def main():<\/p>\n<p>    tasks = [asyncio.create_task(worker(i)) for i in range(5)]<\/p>\n<p>    await asyncio.gather(*tasks)<\/p>\n<p>asyncio.run(main())<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u5b9a\u4e49\u4e86\u4e00\u4e2a\u5f02\u6b65\u51fd\u6570<code>worker<\/code>\uff0c\u5e76\u5728\u4e3b\u51fd\u6570\u4e2d\u521b\u5efa\u4e86\u591a\u4e2a\u4efb\u52a1\u3002\u901a\u8fc7<code>asyncio.gather<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5e76\u53d1\u6267\u884c\u8fd9\u4e9b\u4efb\u52a1\uff0c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6267\u884c\u6548\u7387\u3002<\/li>\n<\/p>\n<\/ul>\n<p><h3>\u4e94\u3001\u5206\u5e03\u5f0f\u8ba1\u7b97<\/h3>\n<\/p>\n<p><p>\u5bf9\u4e8e\u66f4\u5927\u89c4\u6a21\u7684\u8ba1\u7b97\u4efb\u52a1\uff0c\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u5206\u5e03\u5f0f\u8ba1\u7b97\u6846\u67b6\uff0c\u5c06\u4efb\u52a1\u5206\u914d\u5230\u591a\u4e2a\u8ba1\u7b97\u8282\u70b9\u4e0a\u6267\u884c\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>Apache Spark<\/strong>\uff1aSpark\u662f\u4e00\u4e2a\u5206\u5e03\u5f0f\u8ba1\u7b97\u6846\u67b6\uff0c\u652f\u6301\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u548c<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u4efb\u52a1\u3002\u901a\u8fc7Spark\u7684\u9ad8\u7ea7API\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u7f16\u5199\u548c\u6267\u884c\u5206\u5e03\u5f0f\u8ba1\u7b97\u4efb\u52a1\u3002<\/li>\n<li><strong>Ray<\/strong>\uff1aRay\u662f\u4e00\u4e2a\u7528\u4e8e\u5e76\u884c\u548c\u5206\u5e03\u5f0f\u8ba1\u7b97\u7684\u6846\u67b6\uff0c\u652f\u6301\u4efb\u52a1\u8c03\u5ea6\u3001\u8fdc\u7a0b\u51fd\u6570\u8c03\u7528\u548c\u5206\u5e03\u5f0f\u6570\u636e\u5904\u7406\u3002Ray\u63d0\u4f9b\u4e86\u7b80\u6d01\u7684API\uff0c\u65b9\u4fbf\u5f00\u53d1\u8005\u7f16\u5199\u5e76\u884c\u548c\u5206\u5e03\u5f0f\u7a0b\u5e8f\u3002<\/li>\n<li><strong>\u793a\u4f8b\u4ee3\u7801<\/strong>\uff08Ray\uff09\uff1a\n<pre><code class=\"language-python\">import ray<\/p>\n<p>ray.init()<\/p>\n<p>@ray.remote<\/p>\n<p>def worker(num):<\/p>\n<p>    return num * num<\/p>\n<p>futures = [worker.remote(i) for i in range(5)]<\/p>\n<p>results = ray.get(futures)<\/p>\n<p>print(results)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u4f7f\u7528Ray\u5b9a\u4e49\u4e86\u4e00\u4e2a\u8fdc\u7a0b\u51fd\u6570<code>worker<\/code>\uff0c\u5e76\u521b\u5efa\u4e86\u591a\u4e2a\u8fdc\u7a0b\u4efb\u52a1\u3002\u901a\u8fc7<code>ray.get<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u83b7\u53d6\u4efb\u52a1\u7684\u7ed3\u679c\u3002Ray\u4f1a\u81ea\u52a8\u5c06\u4efb\u52a1\u5206\u914d\u5230\u591a\u4e2a\u8ba1\u7b97\u8282\u70b9\u4e0a\u6267\u884c\uff0c\u5b9e\u73b0\u5206\u5e03\u5f0f\u8ba1\u7b97\u3002<\/li>\n<\/p>\n<\/ul>\n<p><h3>\u516d\u3001GPU\u52a0\u901f<\/h3>\n<\/p>\n<p><p>\u5bf9\u4e8e\u9700\u8981\u5927\u91cf\u5e76\u884c\u8ba1\u7b97\u7684\u4efb\u52a1\uff0c\u5982\u6df1\u5ea6\u5b66\u4e60\u548c\u79d1\u5b66\u8ba1\u7b97\uff0c\u53ef\u4ee5\u5229\u7528GPU\u8fdb\u884c\u52a0\u901f\u3002GPU\u5177\u6709\u5927\u91cf\u7684\u8ba1\u7b97\u6838\u5fc3\uff0c\u80fd\u591f\u5728\u77ed\u65f6\u95f4\u5185\u5904\u7406\u5927\u91cf\u6570\u636e\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>CUDA<\/strong>\uff1aCUDA\u662fNVIDIA\u63d0\u4f9b\u7684\u5e76\u884c\u8ba1\u7b97\u5e73\u53f0\u548c\u7f16\u7a0b\u6a21\u578b\uff0c\u53ef\u4ee5\u5229\u7528NVIDIA GPU\u8fdb\u884c\u9ad8\u6548\u7684\u5e76\u884c\u8ba1\u7b97\u3002\u901a\u8fc7CUDA\u7f16\u5199\u7684\u7a0b\u5e8f\u53ef\u4ee5\u5728GPU\u4e0a\u8fd0\u884c\uff0c\u5b9e\u73b0\u5927\u89c4\u6a21\u7684\u5e76\u884c\u8ba1\u7b97\u3002<\/li>\n<li><strong>CuPy<\/strong>\uff1aCuPy\u662f\u4e00\u4e2a\u7528\u4e8eGPU\u52a0\u901f\u7684\u6570\u7ec4\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e0eNumPy\u76f8\u4f3c\u7684\u63a5\u53e3\uff0c\u53ef\u4ee5\u5229\u7528CUDA\u8fdb\u884c\u9ad8\u6548\u7684\u6570\u7ec4\u8fd0\u7b97\u3002<\/li>\n<li><strong>\u793a\u4f8b\u4ee3\u7801<\/strong>\uff08CuPy\uff09\uff1a\n<pre><code class=\"language-python\">import cupy as cp<\/p>\n<p>x = cp.random.random((10000, 10000))<\/p>\n<p>y = x + x.T<\/p>\n<p>result = cp.asnumpy(y)<\/p>\n<p>print(result)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p>\u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u4f7f\u7528CuPy\u521b\u5efa\u4e86\u4e00\u4e2a\u968f\u673a\u6570\u7ec4\uff0c\u5e76\u8fdb\u884c\u4e86\u77e9\u9635\u52a0\u6cd5\u8fd0\u7b97\u3002CuPy\u4f1a\u5229\u7528GPU\u8fdb\u884c\u8ba1\u7b97\uff0c\u63d0\u9ad8\u8ba1\u7b97\u901f\u5ea6\u3002<\/li>\n<\/p>\n<\/ul>\n<p><h3>\u4e03\u3001\u6027\u80fd\u4f18\u5316<\/h3>\n<\/p>\n<p><p>\u9664\u4e86\u4ee5\u4e0a\u63d0\u5230\u7684\u65b9\u6cd5\uff0c\u8fd8\u53ef\u4ee5\u901a\u8fc7\u4f18\u5316\u4ee3\u7801\u548c\u7b97\u6cd5\u6765\u63d0\u9ad8Python\u7a0b\u5e8f\u7684\u6027\u80fd\u3002<\/p>\n<\/p>\n<ul>\n<li><strong>\u7b97\u6cd5\u4f18\u5316<\/strong>\uff1a\u9009\u62e9\u5408\u9002\u7684\u6570\u636e\u7ed3\u6784\u548c\u7b97\u6cd5\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6027\u80fd\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u54c8\u5e0c\u8868\u4ee3\u66ff\u5217\u8868\u67e5\u627e\u3001\u4f7f\u7528\u5feb\u901f\u6392\u5e8f\u4ee3\u66ff\u5192\u6ce1\u6392\u5e8f\u7b49\u3002<\/li>\n<li><strong>\u5185\u5b58\u7ba1\u7406<\/strong>\uff1a\u5408\u7406\u7ba1\u7406\u5185\u5b58\uff0c\u907f\u514d\u4e0d\u5fc5\u8981\u7684\u5185\u5b58\u5206\u914d\u548c\u91ca\u653e\uff0c\u53ef\u4ee5\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6027\u80fd\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u751f\u6210\u5668\u4ee3\u66ff\u5217\u8868\u5b58\u50a8\u5927\u6570\u636e\u96c6\u3001\u4f7f\u7528\u5185\u5b58\u6c60\u51cf\u5c11\u5185\u5b58\u5206\u914d\u7684\u5f00\u9500\u7b49\u3002<\/li>\n<li><strong>\u7f16\u8bd1\u4f18\u5316<\/strong>\uff1a\u901a\u8fc7\u5c06Python\u4ee3\u7801\u7f16\u8bd1\u4e3a\u66f4\u9ad8\u6548\u7684\u5b57\u8282\u7801\u6216\u673a\u5668\u7801\uff0c\u53ef\u4ee5\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6267\u884c\u901f\u5ea6\u3002\u4f8b\u5982\uff0c\u4f7f\u7528Cython\u5c06Python\u4ee3\u7801\u7f16\u8bd1\u4e3aC\u4ee3\u7801\u3001\u4f7f\u7528Numba\u5c06Python\u4ee3\u7801\u7f16\u8bd1\u4e3aLLVM\u5b57\u8282\u7801\u7b49\u3002<\/li>\n<\/ul>\n<p><h3>\u516b\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>Python\u5728\u591a\u6838\u6027\u80fd\u65b9\u9762\u7684\u53d1\u6325\uff0c\u4e3b\u8981\u4f9d\u8d56\u4e8e\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\uff1a<\/p>\n<\/p>\n<ol>\n<li><strong>\u591a\u8fdb\u7a0b<\/strong>\uff1a\u901a\u8fc7\u521b\u5efa\u591a\u4e2a\u72ec\u7acb\u7684\u8fdb\u7a0b\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u5728\u4e0d\u540c\u7684CPU\u6838\u5fc3\u4e0a\u8fd0\u884c\uff0c\u5b9e\u73b0\u5e76\u884c\u8ba1\u7b97\u3002<\/li>\n<li><strong>\u5e76\u884c\u8ba1\u7b97\u5e93<\/strong>\uff1a\u4f7f\u7528NumPy\u3001Dask\u7b49\u5e76\u884c\u8ba1\u7b97\u5e93\uff0c\u7b80\u5316\u5e76\u884c\u8ba1\u7b97\u7684\u5b9e\u73b0\u8fc7\u7a0b\uff0c\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002<\/li>\n<li><strong>\u5f02\u6b65\u7f16\u7a0b<\/strong>\uff1a\u901a\u8fc7\u5f02\u6b65I\/O\u64cd\u4f5c\u548c\u4e8b\u4ef6\u5faa\u73af\uff0c\u5b9e\u73b0\u9ad8\u6548\u7684\u5e76\u53d1\u6267\u884c\uff0c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u54cd\u5e94\u901f\u5ea6\u548c\u5e76\u53d1\u80fd\u529b\u3002<\/li>\n<li><strong>\u5206\u5e03\u5f0f\u8ba1\u7b97<\/strong>\uff1a\u4f7f\u7528Apache Spark\u3001Ray\u7b49\u5206\u5e03\u5f0f\u8ba1\u7b97\u6846\u67b6\uff0c\u5c06\u4efb\u52a1\u5206\u914d\u5230\u591a\u4e2a\u8ba1\u7b97\u8282\u70b9\u4e0a\u6267\u884c\uff0c\u5b9e\u73b0\u5927\u89c4\u6a21\u6570\u636e\u5904\u7406\u548c\u8ba1\u7b97\u3002<\/li>\n<li><strong>GPU\u52a0\u901f<\/strong>\uff1a\u5229\u7528CUDA\u3001CuPy\u7b49\u5de5\u5177\uff0c\u4f7f\u7528GPU\u8fdb\u884c\u9ad8\u6548\u7684\u5e76\u884c\u8ba1\u7b97\uff0c\u52a0\u901f\u6df1\u5ea6\u5b66\u4e60\u548c\u79d1\u5b66\u8ba1\u7b97\u4efb\u52a1\u3002<\/li>\n<li><strong>\u6027\u80fd\u4f18\u5316<\/strong>\uff1a\u901a\u8fc7\u4f18\u5316\u7b97\u6cd5\u3001\u5185\u5b58\u7ba1\u7406\u548c\u7f16\u8bd1\u4f18\u5316\uff0c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6267\u884c\u901f\u5ea6\u548c\u6548\u7387\u3002<\/li>\n<\/ol>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5145\u5206\u5229\u7528\u591a\u6838CPU\u7684\u6027\u80fd\uff0c\u63d0\u9ad8Python\u7a0b\u5e8f\u7684\u6267\u884c\u6548\u7387\u548c\u8ba1\u7b97\u80fd\u529b\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u5e94\u6839\u636e\u4efb\u52a1\u7684\u7279\u70b9\u548c\u9700\u6c42\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u548c\u5de5\u5177\uff0c\u5b9e\u73b0\u5e76\u884c\u548c\u9ad8\u6548\u7684\u8ba1\u7b97\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5229\u7528\u591a\u6838\u5904\u7406\uff1f<\/strong><br \/>Python\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u5229\u7528\u591a\u6838\u5904\u7406\u80fd\u529b\uff0c\u4f8b\u5982\u4f7f\u7528<code>multiprocessing<\/code>\u6a21\u5757\u3001<code>concurrent.futures<\/code>\u6a21\u5757\u6216\u7b2c\u4e09\u65b9\u5e93\u5982<code>Joblib<\/code>\u548c<code>Dask<\/code>\u3002<code>multiprocessing<\/code>\u6a21\u5757\u5141\u8bb8\u60a8\u521b\u5efa\u591a\u4e2a\u8fdb\u7a0b\uff0c\u6bcf\u4e2a\u8fdb\u7a0b\u53ef\u4ee5\u5728\u4e0d\u540c\u7684CPU\u6838\u5fc3\u4e0a\u8fd0\u884c\uff0c\u4ece\u800c\u5b9e\u73b0\u771f\u6b63\u7684\u5e76\u884c\u8ba1\u7b97\u3002\u60a8\u53ef\u4ee5\u901a\u8fc7<code>Process<\/code>\u7c7b\u6765\u542f\u52a8\u65b0\u8fdb\u7a0b\uff0c\u5e76\u901a\u8fc7\u961f\u5217\u6216\u7ba1\u9053\u4e0e\u5b83\u4eec\u901a\u4fe1\u3002<\/p>\n<p><strong>\u4f7f\u7528\u591a\u7ebf\u7a0b\u662f\u5426\u80fd\u63d0\u9ad8Python\u7684\u6027\u80fd\uff1f<\/strong><br \/>Python\u7684\u591a\u7ebf\u7a0b\u80fd\u529b\u53d7\u5230\u5168\u5c40\u89e3\u91ca\u5668\u9501\uff08GIL\uff09\u7684\u9650\u5236\uff0c\u8fd9\u610f\u5473\u7740\u5728\u4efb\u4f55\u65f6\u523b\u53ea\u6709\u4e00\u4e2a\u7ebf\u7a0b\u53ef\u4ee5\u6267\u884cPython\u5b57\u8282\u7801\u3002\u56e0\u6b64\uff0c\u5bf9\u4e8eCPU\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u591a\u7ebf\u7a0b\u5e76\u4e0d\u603b\u662f\u80fd\u63d0\u9ad8\u6027\u80fd\u3002\u7136\u800c\uff0c\u5bf9\u4e8eI\/O\u5bc6\u96c6\u578b\u4efb\u52a1\uff0c\u591a\u7ebf\u7a0b\u53ef\u4ee5\u6709\u6548\u5229\u7528\u7b49\u5f85\u65f6\u95f4\uff0c\u4ece\u800c\u63d0\u9ad8\u7a0b\u5e8f\u7684\u6574\u4f53\u6548\u7387\u3002<\/p>\n<p><strong>\u5728\u6570\u636e\u79d1\u5b66\u9886\u57df\u5982\u4f55\u4f18\u5316Python\u7684\u591a\u6838\u6027\u80fd\uff1f<\/strong><br \/>\u5728\u6570\u636e\u79d1\u5b66\u9886\u57df\uff0c\u4f7f\u7528<code>pandas<\/code>\u3001<code>numpy<\/code>\u7b49\u5e93\u65f6\uff0c\u60a8\u53ef\u4ee5\u901a\u8fc7\u5e76\u884c\u5904\u7406\u6765\u52a0\u901f\u6570\u636e\u5904\u7406\u4efb\u52a1\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u5229\u7528<code>Dask<\/code>\u6765\u5904\u7406\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u5b83\u652f\u6301\u5ef6\u8fdf\u8ba1\u7b97\u548c\u5e76\u884c\u5904\u7406\uff0c\u80fd\u591f\u5728\u591a\u6838\u73af\u5883\u4e2d\u6709\u6548\u5730\u5206\u914d\u8ba1\u7b97\u4efb\u52a1\u3002\u6b64\u5916\uff0c<code>Joblib<\/code>\u5e93\u7684<code>Parallel<\/code>\u51fd\u6570\u4e5f\u53ef\u4ee5\u5e2e\u52a9\u60a8\u8f7b\u677e\u5730\u5728\u591a\u4e2a\u6838\u5fc3\u4e0a\u8fd0\u884c\u5faa\u73af\uff0c\u4ece\u800c\u52a0\u901f\u6570\u636e\u5206\u6790\u8fc7\u7a0b\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u53d1\u6325\u591a\u6838\u6027\u80fd\u7684\u65b9\u6cd5\u6709\u591a\u7ebf\u7a0b\u3001\u591a\u8fdb\u7a0b\u3001\u5e76\u884c\u8ba1\u7b97\u5e93\u3001\u5f02\u6b65\u7f16\u7a0b\u3002\u5176\u4e2d\uff0c\u591a\u8fdb\u7a0b\u662f\u4e00\u79cd\u975e\u5e38\u6709\u6548\u7684\u65b9\u6cd5\u3002Pyt [&hellip;]","protected":false},"author":3,"featured_media":1151653,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1151646"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1151646"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1151646\/revisions"}],"predecessor-version":[{"id":1151655,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1151646\/revisions\/1151655"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1151653"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1151646"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1151646"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1151646"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}