Benchmarks for common python I/O patterns

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Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
35/100
Issue type
Feature
Clarity
Mostly clear
Activity status
Stale
Tech stack
python
Domain
performance

Research direction

Review the existing pyperformance benchmark organization and the proposed I/O shapes in this issue, keeping the scope at the Binary/Bytes IO layer. Define a manually runnable group covering the selected common cases, then verify that it is not enabled by default and that the benchmarks exercise the intended file, stream, archive, import, or concurrency patterns.

Written by the indexing model from the issue text.

Description

As work happens on I/O pieces I've been building specialized micro-benchmarks (ex. gh-120754 Speed up open().read() pattern by reducing the number of system calls and others have gh-117151: IO performance improvement, increase io.DEFAULT_BUFFER_SIZE to 128k), it would be nice to have more general benchmarks to validate I/O performance for common cases.

Talking a little with people at PyConUS there was some interest in the tests, and a general desire for I/O tests not to be enabled by default, but to be a group which can be manually run.

General I/O shapes I'm hoping to add benchmarks for:

  • read/write all of the byes of a file in a single call (including pathlib.Path.read_text, pathlib.Path.write_text)
  • read/write many small files (ex. .pyc files, maybe just compile_all?)
  • streaming bytes read/write (ex. to a pipe / console such as stdin/stdout/stderr, non-seekable devices)
  • read/write a zipfile, tarfile (read + seek, write + seek, in particular buffering behavior)
  • use zipimport
  • Create a zipapp
  • Multi-threaded write to stdout, stderr (ex. logging in a large application/codebase)

Note: With these aiming to stay at the Binary / Bytes IO layer as much as possible (not touch Text I/O for now)

Dominant language
Python
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