codeflash-agent/.codeflash/krrt7/textualize/rich
Kevin Turcios cc29a27289
Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15)
Add team member dimension to case study paths so multiple contributors
can track optimization data independently. Derives member from
git config user.name in session-start hooks.

- Move all case studies under .codeflash/krrt7/
- Rename pypa/pip → python/pip (org grouping)
- Update session-start hooks, docs, scripts, and references
2026-04-14 23:04:34 -05:00
..
bench Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15) 2026-04-14 23:04:34 -05:00
data Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15) 2026-04-14 23:04:34 -05:00
infra Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15) 2026-04-14 23:04:34 -05:00
.gitignore Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15) 2026-04-14 23:04:34 -05:00
README.md Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15) 2026-04-14 23:04:34 -05:00
status.md Migrate .codeflash/ to {teammember}/{org}/{project}/ format (#15) 2026-04-14 23:04:34 -05:00

Rich Performance Optimization

Upstream performance improvements to Textualize/rich, motivated by pip startup time profiling.

Background

pip vendors Rich for its progress bars, logging, and error display. Profiling pip --version revealed Rich as one of the heaviest imports in the startup chain — from rich.console import Console alone took ~79ms on CPython 3.12 (Standard_D2s_v5 VM).

Rather than patching pip's vendored copy, we contributed upstream so everyone benefits.

Results

Import Time (hyperfine, 30+ runs, Standard_D2s_v5)

CPython 3.12

Import master optimized Speedup
Console 79.1 ± 0.8ms 37.5 ± 0.5ms 2.11x
RichHandler 100.3 ± 3.6ms 39.6 ± 0.5ms 2.53x

CPython 3.13

Import master optimized Speedup
Console 67.9 ± 0.7ms 33.6 ± 0.5ms 2.02x
RichHandler 37.5 ± 0.4ms

On Python 3.13+, typing no longer imports re, so deferring all re.compile() calls eliminates re (+ _sre, re._compiler, re._parser, re._constants) from the Console import chain entirely.

Runtime Micro-benchmarks (Python 3.13.13)

Benchmark Before After Speedup
Style.__eq__ (identity) 114ns/call 62ns/call 1.84x
Style.combine (3 styles) 579ns/call 433ns/call 1.34x
Segment.simplify (identity) 1269ns/call 931ns/call 1.36x
Style.chain (3 styles) 959ns/call 878ns/call 1.09x
E2E Console.print 173.7us/call 171.6us/call ~1.01x

What We Changed

PR #12 — Architectural wins (KRRT7/rich#12)

  • Replace @dataclass with __slots__ classesConsoleOptions and ConsoleThreadLocals used @dataclass, which imports inspect at module level (~10ms). Replaced with plain classes + __slots__. ConsoleOptions memory: 344 → 136 bytes (60% reduction).
  • Lazy-load emoji dictionary_emoji_codes.EMOJI (3,608 entries) loaded unconditionally via text.py → emoji.py. Deferred to first use via module-level __getattr__.
  • Defer imports across 12+ modulesinspect, pretty, scope, getpass, configparser, html.escape, zlib, traceback, pathlib → deferred to the methods that actually use them.
  • from __future__ import annotations — Enabled in key modules to allow moving type-only imports to TYPE_CHECKING.

PR #13 — Import deferral + runtime micro-opts (KRRT7/rich#13)

Import deferral (7 files):

  • color.py: RE_COLOR compiled lazily in Color.parse() (LRU-cached)
  • text.py: _re_whitespace lazy; inline import re in 6 methods
  • markup.py: RE_TAGS via _compile_tags(), RE_HANDLER and escape regex lazy
  • _emoji_replace.py: regex default arg → lazy _EMOJI_SUB global
  • _wrap.py: re_word → lazy _re_word
  • highlighter.py: import re inside JSONHighlighter.highlight()
  • default_styles.py: 3 rgb(...) strings → Color.from_rgb() to avoid Color.parse() regex at import

Runtime micro-optimizations:

  • Style.__eq__/__ne__: identity shortcut (is) before hash comparison
  • Style.combine/chain: use _add (LRU-cached) directly instead of sum()__add__.copy() check
  • Segment.simplify: is before == for style comparison

Upstream PR

Methodology

Environment

  • VM: Azure Standard_D2s_v5 (2 vCPU, 8 GB RAM, non-burstable)
  • OS: Ubuntu 24.04 LTS
  • Region: westus2
  • Python: 3.12 and 3.13 via uv
  • Tooling: hyperfine (warmup 5, min-runs 30), timeit (best of 7)

Non-burstable VM chosen for consistent CPU performance — no thermal throttling or turbo variability.

Benchmark harness

All scripts in bench/:

Script Purpose
bench_import.sh Overall import rich time via hyperfine
bench_module.sh Per-module import time (Console, RichHandler, Traceback, etc.)
bench_e2e.sh A/B comparison: master vs optimized branch
bench_compare.sh Generic branch comparison wrapper
bench_importtime.py python -X importtime parser → sorted TSV breakdown
bench_runtime.py PR #12 runtime benchmarks (ConsoleOptions, emoji_replace)
bench_runtime2.py PR #13 runtime benchmarks (Style.eq, combine, Segment.simplify)
bench_text.py Text hot-path benchmarks (construction, copy, divide, render)
test_all_impls.sh Run tests across CPython 3.93.14 + PyPy 3.10

Raw data

Hyperfine JSON exports in data/.

Maintainer Engagement

Reached out to Will McGugan (Textualize CEO) via Discord. Conversation in discord-transcript.md.

Key quotes:

  • "Seems like a clear win. Feel free to open a PR."
  • "I'd say single PR."

Repo Structure

.
├── README.md              # This file
├── cloud-init.yaml        # VM provisioning (one-shot reproducible setup)
├── discord-transcript.md  # Will McGugan conversation
├── bench/                 # Benchmark scripts (from VM)
│   ├── bench_import.sh
│   ├── bench_module.sh
│   ├── bench_e2e.sh
│   ├── bench_compare.sh
│   ├── bench_importtime.py
│   ├── bench_runtime.py
│   ├── bench_runtime2.py
│   ├── bench_text.py
│   └── test_all_impls.sh
├── data/                  # Raw benchmark data (hyperfine JSON)
│   ├── e2e-3.12/
│   └── runtime/
└── vm-setup.md            # Azure VM provisioning instructions