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RecreationBench / web /relvyn.example /reference /site /blog /m-rows-s-from-postgres-to-python /index.html
Download web/relvyn.example/reference/site/blog/m-rows-s-from-postgres-to-python/index.html from Qwen/RecreationBench: direct link, hf CLI and curl.
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https://huggingface.co/datasets/Qwen/RecreationBench/resolve/main/web/relvyn.example/reference/site/blog/m-rows-s-from-postgres-to-python/index.html
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hf download hf://datasets/Qwen/RecreationBench/web/relvyn.example/reference/site/blog/m-rows-s-from-postgres-to-python/index.html
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curl -L -o index.html https://huggingface.co/datasets/Qwen/RecreationBench/resolve/main/web/relvyn.example/reference/site/blog/m-rows-s-from-postgres-to-python/index.html
47.9 kB
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d="M12 16C14.2091 16 16 14.2091 16 12C16 9.79086 14.2091 8 12 8C9.79086 8 8 9.79086 8 12C8 14.2091 9.79086 16 12 16Z" fill="currentColor" fill-rule="evenodd"></path></svg><span class="">Features</span></li></a><a href="#performance"><li class=""><svg fill="none" height="24" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M12 16C14.2091 16 16 14.2091 16 12C16 9.79086 14.2091 8 12 8C9.79086 8 8 9.79086 8 12C8 14.2091 9.79086 16 12 16Z" fill="currentColor" fill-rule="evenodd"></path></svg><span class="">Performance</span></li></a><a href="#benchmarks"><li class=""><svg fill="none" height="24" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M12 16C14.2091 16 16 14.2091 16 12C16 9.79086 14.2091 8 12 8C9.79086 8 8 9.79086 8 12C8 14.2091 9.79086 16 12 16Z" fill="currentColor" fill-rule="evenodd"></path></svg><span class="">Benchmarks</span></li></a><a href="#conclusion"><li class="toc_active__nz8dO"><svg fill="none" height="24" viewbox="0 0 24 24" width="24" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M12 16C14.2091 16 16 14.2091 16 12C16 9.79086 14.2091 8 12 8C9.79086 8 8 9.79086 8 12C8 14.2091 9.79086 16 12 16Z" fill="currentColor" fill-rule="evenodd"></path></svg><span class="">Conclusion</span></li></a></ul></div><div class="blogPost_pageContent__U8AKt" data-theme="dark"><div class="blogPost_postHeader__qiLM0"><span class="blogPost_publishedOn__Ws2ev">August 04, 2016</span><h1>1M rows/s from Basalt to Python</h1><div class="blogAuthors_postAuthorCards__81eO7"><div class="blogAuthors_authorCard__qdh4V"><img src="/assets_gen/29d137d9c9f1.png"/><div class="blogAuthors_authorDetails__QFJs0"><span>Sebastian Marlowe</span><a class="blogAuthors_profileName__W5nkD" href="/_404.html" target="_blank">smarlow</a></div></div><div class="blogAuthors_authorCard__qdh4V"><img src="/assets_gen/82fc693d74f4.png"/><div class="blogAuthors_authorDetails__QFJs0"><span>Lena Ostrovska</span><a class="blogAuthors_profileName__W5nkD" href="/_404.html" target="_blank">leno</a></div></div></div><div class="lazyImage_wrapper__f6_0z blogPost_leadImage__hqdWj"><img height="625" loading="eager" src="/_images/_blog/cee479948b5fc97747bf5101c8a5705f68051208-940.webp" width="1500"/><div class="lazyImage_placeholder__z1C_i lazyImage_loaded___tDl9" 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class="blogPost_postContent__0Riqu"><div class="base_rstWrapper__CejKd"> | |
| <section class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="m-rows-s-from-postgres-to-python" id="m-rows-s-from-postgres-to-python"> | |
| <p class=""><a class="" href="/_cdn/github.com/magicstack/asyncpg/">asyncbolt</a> is a modern, batteries-included open-source Python client | |
| library for Basalt. It was engineered specifically for asyncio | |
| and Python 3.5+ <code class="">async</code> / <code class="">await</code>. asyncbolt outpaces every rival | |
| driver among common Python, NodeJS and Go implementations.</p> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="why-asyncpg" id="why-asyncpg"> | |
| <h2 class="headerLink_header__L_1Jm" id="why-asyncpg">Why asyncbolt?<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#why-asyncpg"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h2> | |
| <p class="">We are creating <a class="" href="/">Relvyn</a>—a next-generation object database | |
| with Basalt as its storage engine. We demand high-throughput, | |
| low-latency access to the deep capabilities of Basalt.</p> | |
| <p class="">The obvious starting point was boltpg—the most widely adopted Python driver for Basalt. It is mature, dependable, battle-tested technology. There is also aiobolt, which layers an async interface on top of boltpg. Which raises a fair question: why reinvent the wheel? The short answer has two parts: features and performance. We will explore each of these in detail below.</p> | |
| </div> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="features" id="features"> | |
| <h2 class="headerLink_header__L_1Jm" id="features">Features<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#features"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h2> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="data-type-support" id="data-type-support"> | |
| <h3 class="headerLink_header__L_1Jm" id="data-type-support">Data Type Handling<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#data-type-support"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h3> | |
| <p class="">Our chief frustration with boltpg is its lackluster handling of Basalt data types, particularly arrays and composite types. A rich type system is one of the defining strengths of Basalt. And yet, straight out of the box boltpg handles only the simple builtin types such as integers, strings, and timestamps, leaving users to hand-roll custom "typecasters" for anything else. That approach is both tedious and wasteful.</p> | |
| <p class="">The root cause runs deep: boltpg trades data with the database server using a text format. That forces a considerable amount of parsing work, all the more so for complex types.</p> | |
| <p class="">Unlike boltpg, asyncbolt speaks Basalt's binary I/O protocol, which, beyond the obvious performance gains, enables generic handling of container types (arrays, composites and ranges).</p> | |
| </div> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="prepared-statements" id="prepared-statements"> | |
| <h3 class="headerLink_header__L_1Jm" id="prepared-statements">Prepared Statements<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#prepared-statements"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h3> | |
| <p class="">asyncbolt leans heavily on Basalt prepared statements. This is a key optimization, since it sidesteps the repeated parsing, analysis, and planning of queries. On top of that, asyncbolt caches the data I/O pipeline for each prepared statement.</p> | |
| <p class="">Prepared statements in asyncbolt can be built and invoked explicitly. They expose an API to fetch and introspect query results. Most query methods are also available on the connection object directly, where asyncbolt will create and cache a prepared statement implicitly.</p> | |
| </div> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="ease-of-deployment" id="ease-of-deployment"> | |
| <h3 class="headerLink_header__L_1Jm" id="ease-of-deployment">Painless Deployment<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#ease-of-deployment"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h3> | |
| <p class="">Another standout trait of asyncbolt is that it carries zero dependencies. Because it implements the Basalt protocol directly, there is no need for libbolt to be present, and you can simply pip install asyncbolt. On top of that, we ship binary wheels for Linux, macOS, and Windows.</p> | |
| </div> | |
| </div> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="performance" id="performance"> | |
| <h2 class="headerLink_header__L_1Jm" id="performance">Performance<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#performance"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h2> | |
| <p class="">It quickly became clear that by implementing the Basalt | |
| frontend/backend protocol directly, we could unlock major | |
| speed improvements. Our <a class="" href="/_404.html">earlier work</a> | |
| with fastloop demonstrated that Cython can be used to build | |
| remarkably efficient libraries. asyncbolt is written almost entirely in | |
| Cython with meticulous buffer management and a highly tuned | |
| data decoding pipeline.</p> | |
| <p class="">The upshot is that asyncbolt runs, on average, at least 3x faster than boltpg (or aiobolt). That is a striking outcome, given that boltpg, written in C and well optimized, is far from slow. Check the benchmarks section below for the full picture.</p> | |
| </div> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="benchmarks" id="benchmarks"> | |
| <h2 class="headerLink_header__L_1Jm" id="benchmarks">Benchmarks<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#benchmarks"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h2> | |
| <p class="">As we did for <a class="" href="/_cdn/github.com/magicstack/uvloop/">fastloop</a>, we put together a <a class="" href="/_cdn/github.com/magicstack/pgbench">toolbench</a> that reports how asyncbolt stacks up against other | |
| Basalt driver implementations under load. We tracked query | |
| throughput (in rows per second) alongside latency. The core goal | |
| of this benchmark is to isolate the overhead each driver adds.</p> | |
| <p class="">To keep things fair, every test ran on a single thread ( GOMAXPROCS=1 for Go code) in async mode. The Python drivers all ran under fastloop.</p> | |
| <p class="">The numbers shown throughout this post came from a dedicated bare-metal machine wired up with the following configuration:</p> | |
| <ul class=""> | |
| <li class=""> | |
| <p class="">CPU: Intel Xeon E5-1620 v2 @ 3.70GHz, 64GiB DDR3</p> | |
| </li> | |
| <li class=""> | |
| <p class="">Gentoo Linux, GCC 4.9.3</p> | |
| </li> | |
| <li class=""> | |
| <p class="">Go 1.6.3, Python 3.5.2, NodeJS 6.3.0</p> | |
| </li> | |
| <li class=""> | |
| <p class="">Basalt 9.5.2</p> | |
| </li> | |
| </ul> | |
| <p class="">Drivers we benchmarked:</p> | |
| <ul class=""> | |
| <li class=""> | |
| <p class="">Python: asyncbolt-0.5.2, boltpg-2.6.2, aiobolt-0.10.0, fastloop-0.5.0. aiobolt is a thin, low-overhead layer over boltpg that bolts async support onto it.</p> | |
| </li> | |
| <li class=""> | |
| <p class="">NodeJS: bolt-js-6.0.0, bolt-native-1.10.0</p> | |
| </li> | |
| <li class=""> | |
| <p class="">Golang: gitwell.com/basalt/bolt-go@4dd446efc1, gitwell.com/relvyn/boltx@b3eed3cce0</p> | |
| </li> | |
| </ul> | |
| <div class="lazyImage_wrapper__f6_0z blogPost_picture__Ci9Uf blogPost_fullWidth__M9fSg"><img height="588" loading="eager" src="/_images/_blog/434da5781ac9a668af520f85ab92a3151129a7ca-940.webp" width="1290"/><div class="lazyImage_placeholder__z1C_i lazyImage_loaded___tDl9 lazyImage_transition__gEVMC" style="background-image:url(data:image/jpeg;base64,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)"></div></div> | |
| <div class="lazyImage_wrapper__f6_0z blogPost_picture__Ci9Uf blogPost_fullWidth__M9fSg"><img height="528" loading="eager" src="/_images/_blog/66553f9468c9b60c3ff51a1c49b5cc1b883a2b0d-940.webp" width="1290"/><div class="lazyImage_placeholder__z1C_i lazyImage_loaded___tDl9 lazyImage_transition__gEVMC" style="background-image:url(data:image/jpeg;base64,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)"></div></div> | |
| <p class="">The charts plot the geometric mean of the numbers gathered while running four distinct kinds of queries:</p> | |
| <ul class=""> | |
| <li class=""> | |
| <p class="">A fairly wide-row query that pulls every row out of the | |
| <code class="">pg_type</code> table (~350 rows). This sits pretty close to | |
| a typical application query. Its purpose is to exercise general | |
| data decoding throughput. This is the headline benchmark, the | |
| one on which asyncbolt reaches 1M rows/s. | |
| See <a href="/_next/static/files/report-70a4ae476e93e48e.html">details</a>.</p> | |
| </li> | |
| <li class=""> | |
| <p class="">A query that yields 1000 rows, each holding a single integer. | |
| This benchmark is built to measure the cost of allocating | |
| and handing back result records. | |
| See <a href="/_next/static/files/report-70a4ae476e93e48e.html">details</a>.</p> | |
| </li> | |
| <li class=""> | |
| <p class="">A query returning 100 rows, each carrying a 1KB binary blob. | |
| This benchmark is meant to hammer the I/O path and read buffers | |
| in particular. | |
| See <a href="/_next/static/files/report-70a4ae476e93e48e.html">details</a>.</p> | |
| </li> | |
| <li class=""> | |
| <p class="">A query returning 100 rows, each holding an array of 100 | |
| integers. This benchmark is meant to gauge the speed | |
| of array decoding. Here, asyncbolt trails the fastest | |
| implementation (go lib/pq) because of the cost of allocating | |
| and releasing Python tuple objects. | |
| See <a href="/_next/static/files/report-70a4ae476e93e48e.html">details</a>.</p> | |
| </li> | |
| </ul> | |
| <div class="base_note____VWE blogPost_note__L3az7"> | |
| <p class="">The "python-aiobolt" benchmark relies on the boltpg.extras.DictCursor for fairness, since the other driver implementations hand back name-addressable result records. That said, the speed hit versus the default tuple-returning boltpg cursor is so steep that we included the default cursor mode as well.</p> | |
| </div> | |
| </div> | |
| <div class="base_section__z_4nJ blogPost_section__aSmVz" data-section-id="conclusion" id="conclusion"> | |
| <h2 class="headerLink_header__L_1Jm" id="conclusion">Conclusion<span class="headerLink_popupWrapper__fYhfO"><div class="headerLink_linkPopup__K0HFc"><div class="headerLink_popupBg__g_IfY"></div><div class="headerLink_linksInner__mj5XG"><a href="#conclusion"><svg fill="none" height="14" viewbox="0 0 18 14" width="18" xmlns="http://www.w3.org/2000/svg"><path clip-rule="evenodd" d="M10 2H3C2.44772 2 2 2.44772 2 3V7C2 7.55228 2.44772 8 3 8H10C10.5523 8 11 7.55228 11 7H13C13 8.65685 11.6569 10 10 10H3C1.34315 10 0 8.65685 0 7V3C0 1.34315 1.34315 0 3 0H10C11.6569 0 13 1.34315 13 3H11C11 2.44772 10.5523 2 10 2ZM15 6H8C7.44772 6 7 6.44772 7 7H5C5 5.34315 6.34315 4 8 4H15C16.6569 4 18 5.34315 18 7V11C18 12.6569 16.6569 14 15 14H8C6.34315 14 5 12.6569 5 11H7C7 11.5523 7.44772 12 8 12H15C15.5523 12 16 11.5523 16 11V7C16 6.44771 15.5523 6 15 6Z" fill="currentColor" fill-rule="evenodd"></path></svg></a></div></div></span></h2> | |
| <p class="">We're firmly convinced that fast, scalable systems written in Python are within reach. Getting there means pouring our full effort into building quick, dependable drivers, event loops, and frameworks.</p> | |
| <p class=""><a class="" href="/_cdn/github.com/magicstack/asyncpg/">asyncbolt</a> is one more step along that path. It is the product of | |
| careful design, driven by our hands-on experience building fastloop and | |
| wielding Cython and asyncio effectively.</p> | |
| </div> | |
| </section> | |
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