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\u4e0a\u8ff0\u73b0\u8c61\u5176\u5b9e\u5df2\u7ecf\u89c2\u5bdf\u5230\u5f88\u591a\u6b21\u4e86\uff0c\u4e5f\u6709\u5f88\u957f\u65f6\u95f4\u4e86\uff0c\u4f46\u671f\u95f4\u4e00\u76f4\u6ca1\u6709\u82b1\u65f6\u95f4\u53bb\u8c03\u7814\u8fd9\u4e2a\u95ee\u9898\u3002\u662f\u5728\u4e0d\u5e94\u8be5\u3002<\/p>\n\n\n\n
Python\u91cc\u9762\u5f15\u5165\u4e00\u4e2a\u673a\u5236GIL\uff08global interpreter lock<\/strong>\uff09\uff0c\u8bb0\u5168\u5c40\u89e3\u91ca\u5668\u9501\uff0c\u4ed6\u4f1a\u8ba9\u540c\u4e00\u65f6\u523b\uff0c\u53ea\u6709\u4e00\u4e2a\u7ebf\u7a0b\u6267\u884cpython\u4ee3\u7801\u3002\u4e5f\u5c31\u662f\u5b83\u7ed9\u89e3\u91ca\u5668\u52a0\u4e86\u4e00\u628a\u9501\uff0c\u907f\u514d\u5728\u591a\u7ebf\u7a0b\u73af\u5883\u4e0b\u51fa\u7684\u5404\u79cd\u95ee\u9898\u3002\u7b97\u662f\u4e00\u79cd\u8bbe\u8ba1\u4e0a\u7684\u5747\u8861\u8003\u91cf\u3002<\/p>\n\n\n\n The mechanism used by the CPython<\/a> interpreter to assure that only one thread executes Python bytecode<\/a> at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as However, some extension modules, either standard or third-party, are designed so as to release the GIL when doing computationally intensive tasks such as compression or hashing. Also, the GIL is always released when doing I\/O.<\/p>\n\n\n\n Past efforts to create a \u201cfree-threaded\u201d interpreter (one which locks shared data at a much finer granularity) have not been successful because performance suffered in the common single-processor case. It is believed that overcoming this performance issue would make the implementation much more complicated and therefore costlier to maintain.<\/p>\n<\/blockquote>\n\n\n\n \u80cc\u666f \u5de5\u4f5c\u8fc7\u7a0b\u4e2d\u89c2\u5bdf\u5230\u8fd9\u4e48\u4e00\u4e2a\u73b0\u8c61\uff1apython+flask\u8fd9\u5bf9\u642d\u6863\u4e2d\uff0c\u5f53\u4e00\u4e2arequest\u8fdb\u6765\u89e6\u53d1\u4e00\u4e2a\u957f\u65f6\u95f4 … \u9605\u8bfb\u66f4\u591a<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[54,24],"class_list":["post-201","post","type-post","status-publish","format-standard","hentry","category-7","tag-gil","tag-python"],"_links":{"self":[{"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=\/wp\/v2\/posts\/201","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=201"}],"version-history":[{"count":1,"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=\/wp\/v2\/posts\/201\/revisions"}],"predecessor-version":[{"id":202,"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=\/wp\/v2\/posts\/201\/revisions\/202"}],"wp:attachment":[{"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=201"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=201"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.road-trip.cc\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=201"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
dict<\/code><\/a>) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines.<\/p>\n\n\n\n\u6446\u8131\u9650\u5236<\/h2>\n\n\n\n
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\u591a\u8fdb\u7a0b\u6a21\u578b<\/h2>\n\n\n\n
import concurrent.futures\nimport math\n\nPRIMES = [\n 112272535095293,\n 112582705942171,\n 112272535095293,\n 115280095190773,\n 115797848077099,\n 1099726899285419]\n\ndef is_prime(n):\n if n < 2:\n return False\n if n == 2:\n return True\n if n % 2 == 0:\n return False\n\n sqrt_n = int(math.floor(math.sqrt(n)))\n for i in range(3, sqrt_n + 1, 2):\n if n % i == 0:\n return False\n return True\n\ndef main():\n with concurrent.futures.ProcessPoolExecutor() as executor:\n for number, prime in zip(PRIMES, executor.map(is_prime, PRIMES)):\n print('%d is prime: %s' % (number, prime))\n\nif __name__ == '__main__':\n main()<\/code><\/pre>\n\n\n\n\u53c2\u8003\u8d44\u6599<\/h2>\n\n\n\n
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