chore(deps): bump black from 26.3.1 to 26.5.0

[dependabot]

Bumps black from 26.3.1 to 26.5.0.

Release notes

Sourced from black's releases.

26.5.0

Highlights

• Add support for unpacking in comprehensions (PEP 798) and for lazy imports (PEP 810), both new syntactic features in Python 3.15 (#5048)
• Python 3.15 is now supported. Compiled wheels are not yet provided for Python 3.15, so performance may be slower than on existing Python versions. Wheels will be provided once Python 3.15 is later in its release cycle. (#5127)

Stable style

• Fix # fmt: skip being ignored in nested if expressions with parenthesized in clauses (#4903)
• Add syntactic support for Python 3.15 (#5048)
• Fix crash when an f-string follows a # fmt: off comment inside brackets (#5097)
• Preserve multiline compound statement headers when # fmt: skip is placed on the colon line (#5117)

Preview style

• Improve heuristics around whether blank lines should appear before, within and after groups of same-name decorated functions (such as @overload groups) in .pyi stub files (#5021)
• Fix blank lines being removed between a function and a decorated class in .pyi stub files (#5092)
• Prevent string merger from creating unsplittable long lines when a pragma comment (e.g. # type: ignore) follows the closing bracket (#5096)

Packaging

• Run CI on 3.15 (#5127)

Output

• Improve parse error readability by showing multi-line output with an error pointer. (#5068)
• Add SourceASTParseError to distinguish source parse failures from internal safety errors, improving error reporting when Black's lenient parser accepts input that ast.parse() rejects (#5080)

Blackd

• Return HTTP 400 (Bad Request) for source parse failures instead of HTTP 500, keeping HTTP 500 only for genuine internal safety errors (#5080)

Integrations

• Added documentation for doctest formatting tools and updated the integrations index to match (#4916)

... (truncated)

Changelog

Sourced from black's changelog.

Version 26.5.0

Highlights

• Add support for unpacking in comprehensions (PEP 798) and for lazy imports (PEP 810), both new syntactic features in Python 3.15 (#5048)
• Python 3.15 is now supported. Compiled wheels are not yet provided for Python 3.15, so performance may be slower than on existing Python versions. Wheels will be provided once Python 3.15 is later in its release cycle. (#5127)

Stable style

• Fix # fmt: skip being ignored in nested if expressions with parenthesized in clauses (#4903)
• Add syntactic support for Python 3.15 (#5048)
• Fix crash when an f-string follows a # fmt: off comment inside brackets (#5097)
• Preserve multiline compound statement headers when # fmt: skip is placed on the colon line (#5117)

Preview style

• Improve heuristics around whether blank lines should appear before, within and after groups of same-name decorated functions (such as @overload groups) in .pyi stub files (#5021)
• Fix blank lines being removed between a function and a decorated class in .pyi stub files (#5092)
• Prevent string merger from creating unsplittable long lines when a pragma comment (e.g. # type: ignore) follows the closing bracket (#5096)

Packaging

• Run CI on 3.15 (#5127)

Output

• Improve parse error readability by showing multi-line output with an error pointer. (#5068)
• Add SourceASTParseError to distinguish source parse failures from internal safety errors, improving error reporting when Black's lenient parser accepts input that ast.parse() rejects (#5080)

Blackd

• Return HTTP 400 (Bad Request) for source parse failures instead of HTTP 500, keeping HTTP 500 only for genuine internal safety errors (#5080)

Integrations

• Added documentation for doctest formatting tools and updated the integrations index to match (#4916)

... (truncated)

Commits

• d2490e2 Prepare release 26.5.0 (#5131)
• 2b13ea7 Preserve multiline headers with fmt skip (#5117)
• aef52e0 Improve fmt:skip handling in nested expressions with checks (#4903)
• 9e87495 Add CI coverage for Python 3.15 (#5127)
• 9fd9ea2 Fix blackd error handling: split SourceASTParseError from ASTSafetyError (#5080)
• 866c350 Bump docutils, sphinx, myst-parser (#4960)
• 05b4d1e docs: update deprecated PEP URLs to peps.python.org (#5115)
• 1c25a47 [pre-commit.ci] pre-commit autoupdate (#5111)
• b0fa37f Bump zizmorcore/zizmor-action from 0.5.2 to 0.5.3 (#5109)
• 530d5ab Bump actions/cache from 5.0.4 to 5.0.5 (#5108)
• Additional commits viewable in compare view

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[github-actions]

NeuralMind self-benchmark

Status: PASS — floor 4×, measured 5.9×.

Phase 1 — Reduction on committed fixture

• Average reduction: 5.9×
• Top-k retrieval hit rate: 71.7%
• Naive baseline: 47,360 tokens (all fixture files concatenated)
• NeuralMind total: 8,149 tokens across 10 queries
• Estimated monthly savings @ 100 queries/day on Claude 3.5 Sonnet: ~$35.30

#	Query	Shape	Naive	NeuralMind	Ratio	Hit
1	auth-flow	cross-file	4,736	815	5.8×	33.3%
2	api-endpoints	focused	4,736	809	5.9×	100.0%
3	billing-flow	cross-file	4,736	846	5.6×	33.3%
4	user-storage	cross-file	4,736	672	7.0×	50.0%
5	jwt-verify	focused	4,736	681	7.0×	100.0%
6	stripe-webhook	focused	4,736	838	5.7×	100.0%
7	create-user	cross-file	4,736	794	6.0×	50.0%
8	refund	focused	4,736	827	5.7×	100.0%
9	db-choice	identity	4,736	899	5.3×	100.0%
10	invoice-send	cross-file	4,736	968	4.9×	50.0%

Phase 2 — Learning uplift

• Memory events logged: 20
• Learned patterns: 20
• Reduction ratio after neuralmind learn: 5.9× (Δ +0.00× vs. cold)
• Top-k hit rate after learning: 71.7% (Δ +0.0 points vs. cold)

Note: uplift numbers on a 500-line fixture are intentionally modest — the point is to
verify the learning mechanism persists and applies. On real production repos the lift
is larger; this test only catches regressions in persistence.

Assumptions

• Baseline: every .py file in tests/fixtures/sample_project/ concatenated.
• Tokenizer: tiktoken GPT-4o encoding (per-model breakdown in multi_model.json if generated).
• Pricing: Claude 3.5 Sonnet input @ $3.0/MTok.
• Regression floor: 4× — well below NeuralMind's typical 40–70× on real repos.

Per-model token reduction

Model	Tokenizer	Naive	NeuralMind	Ratio	Source
GPT-4o / GPT-4o-mini	tiktoken o200k_base	4,739	927	5.1×	measured
GPT-4 / GPT-3.5-turbo	tiktoken cl100k_base	4,710	918	5.1×	measured
Claude 3.5 Sonnet	estimated: GPT-4o × 1.08 — install anthropic for an exact count	5,118	1,001	5.1×	estimated
Llama 3 (70B)	estimated: GPT-4o × 1.22 — Llama tokenizer requires model weights; estimate based on published vocab ratios	5,781	1,130	5.1×	estimated

Rows marked measured use the provider's real tokenizer. Rows marked
estimated apply a published vocab-size correction to the GPT-4o count —
honest approximations, not hardcoded claims.

---

Automated by .github/workflows/ci-benchmark.yml — regenerate locally with python -m tests.benchmark.run.