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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## master #14316 +/- ##
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Coverage 99.11% 99.12%
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Files 135 135
Lines 53439 54138 +699
Branches 2723 2779 +56
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+ Hits 52967 53664 +697
- Misses 358 360 +2
Partials 114 114
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Merging this PR will improve performance by 36.92%3 warnings
Performance Changes
Tip Curious why performance improved? Comment Comparing Footnotes
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[Medium impact] The PR appears safe to merge; all four numbered findings are addressed. Reviews (5) · Last reviewed commit: "Fix executor decompression shutdown, err..." · Reviewed by Greptile |
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Missed the remaining coverage issue, fixing that now. |
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@codspeedbot explain why performance improved |
I compared the CodSpeed Simulation flamegraphs for this PR's head ( Moving work to the executor doesn't hide itSimulation adds up CPU time from every thread, and the executor threads show up in the profile. In Where the time went: copying in
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memcpy caller (base) |
Time |
|---|---|
StreamReader._read_nowait (b"".join(chunks)) |
42.2 ms |
StreamReader._read_nowait_chunk (first_buffer[offset:offset+n]) |
37.3 ms |
_int_realloc inside isal_zlib decompress |
~36 ms |
Here is what happened on master during iter_chunked(1 MiB):
_read_nowait_chunk()drops the buffer below the low-water mark and callsresume_reading().- That call goes straight into
data_received()→feed_data()→DeflateBuffer.feed_data()and decompresses the next block synchronously while the read is still in progress. - The
while self._buffer:loop in_read_nowait()then finds the freshly added data. It slices the partially read large chunk, which copies it, and finally runsb"".join(chunks)over several MB, which copies it again.
With offloading, resume_reading() → DeflateBuffer.feed_data() only queues the next decode with run_in_executor and pauses reading. Nothing new reaches the buffer during the read. _read_nowait() now usually returns a single buffered chunk without slicing or joining. On the head, StreamReader.read dropped from 145.2 ms to 0.63 ms, and the memcpy under it is gone. realloc inside the decompressor also halved (~36 ms → ~18 ms).
The new cost of offloading on the event loop is small: run_in_executor, ThreadPoolExecutor.submit, Condition/Future locking and the extra call_soon_threadsafe wakeups come to well under 1 ms per run here.
The zlib-ng and [zlib] variants of the same benchmark, and test_get_request_with_251308_compressed_chunked_payload, improve the same way. They gain less because the decompressor's own work makes up more of their total.
Caveats
test_read_compressed_post_body[*](+15–16%) is probably not from this PR. It measures the server:web_protocol's request parser doesn't getoffload_decompression, and the flamegraph still shows decompression inline incb_on_body. The whole difference is inmemcpy/realloccost.- CodSpeed reported that the base and head ran on different CPUs (EPYC 9V74 → 9V45) and that the compiled
.sobuild IDs changed, for all 7 improved benchmarks. That explains changes like the server one above. It doesn't explain the client wins, because those come from code paths that are gone on the head. - Most of these benchmarks are dominated by system calls, which Simulation excludes. Simulation also measures total CPU work, not how much runs in parallel, so the throughput gain you saw locally with many requests in parallel won't show up in these numbers. You'd need Walltime on macro runners for that.
- The win in
iter_chunkedpartly comes from a side effect: reading no longer re-enters decompression synchronously. You could get some of that win in the synchronous path too, for example by not callingresume_reading()from inside_read_nowait_chunk()while a multi-chunk read is still running. Then the speedup wouldn't depend on offloading.
Comparison: https://app.codspeed.io/aio-libs/aiohttp/runs/compare/6af4c9209c0b923757c59ac5..6af603624cee452e9b868112
Comment @codspeedbot try avoiding the re-entrant decompression in StreamReader._read_nowait without offloading if you want me to try that change and benchmark it on its own.
Summary
- Warming up the performance wizard...
- Handling comment — Comment handling finished successfully
Was this response helpful? React with 👍 or 👎 to help us improve CodSpeedBot.
PR Review — Add optional executor offloading for client response decompressionSolid, carefully tested mechanism, but the PR head silently turned the opt-in feature into always-on with no escape hatch, and the title/description/request-level docs still describe the opt-in version. What is done well: the offload reuses the existing pause/continuation protocol instead of adding a parallel path, keeps exactly one worker per response, and preserves output limits and chunk-count backpressure. The deferred-EOF state is cleaned up consistently across
🟡 Important
1. Offloading is now unconditional with no opt-out, contradicting the PR title/description
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What do these changes do?
Add
auto_decompress_in_executorto ClientSession and individual requests, allowing automatic response decompression to run in the event loop's default thread pool.The implementation reuses the parser continuation mechanism, preserves streaming and backpressure, and supports all existing content encodings. Includes regression tests, a precompressed-response benchmark, documentation, and a threat-model update.
Are there changes in behavior for the user?
Existing behavior remains unchanged by default. Users can enable offloading for a session or a single request by passing
auto_decompress_in_executor=True.I'm still wondering whether it shouldn't just be enabled by default, as the measured offloading overhead was rather small locally, and the gains when processing many requests in parallel showed an increase in throughput of around 65%.
I suppose codspeed will tell us more when it runs on this PR :)
Is it a substantial burden for the maintainers to support this?
The change adds asynchronous decompression lifecycle handling across the Python and Cython parsers, particularly around connection loss, EOF, errors, and response cleanup. It uses the existing decompressor implementations and parser continuation mechanism without adding dependencies.
Tests cover both parser implementations, supported encodings, output backpressure, chunk boundaries, pending work during connection loss, decoding errors, cancellation, and connection reuse.
Related issue number
None.
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