```布洛普语言```

```布洛普语言```
Blorp Language

Blorp 是一门高性能、低损耗的编程语言，专为可靠性、可读性和速度而设计。通过编译为 C 代码，它在提供更安全、现代的开发体验的同时，实现了媲美手写 C 代码的性能。核心特性包括： * **安全性与可预测性：** 该语言利用强静态类型、穷举模式匹配、显式故障处理和纯度追踪来最大限度地减少错误。 * **直观语法：** Blorp 强调简洁、可读的语法，无论对人类开发者还是人工智能助手而言，都简单易懂。 * **高性能：** 它利用值语义、ARC/COW（写时复制）内存管理以及 Perceus 风格的所有权分析，确保资源的高效利用。 * **现代并发：** 结构化并发工具（如作用域任务和通道）确保并发操作既安全、受控，又易于理解。 * **编译时保证：** 通过固定维度边界和严格的类型检查，编译器可在执行前证明数组索引等操作的安全性。总而言之，Blorp 平衡了高级语言的“直观性”与底层系统语言的显式控制及原生速度，使其成为构建耐用、高性能软件的理想选择。

Sorry.

原文

A low-friction, high-performance language for code you can trust.

GOALS = [
	("confidence", ["pure functions", "explicit effects"]),
	("speed", ["native code", "structured concurrency"]),
	("approachability", ["small syntax", "direct control flow"]),
	("durability", ["typed failure", "safe bounds"]),
]


pure func format_goal(goal: (String, List[String])) -> String:
	(name, features) = goal
	"${name}: ${features.join(", ")}"


func main(args: List[String]):
	pitch = GOALS
		.map(format_goal)
		.join("\n")

	print(pitch)

Features

Blorp keeps the language surface direct while making effects, failure, and concurrency easier to reason about.

Readable syntaxIndentation, keyword operators, and method-style calls keep code easy to scan.
Static safetyStrong types, checked imports, explicit fallibility, and exhaustive match make mistakes harder to hide.
Purity trackingpure func separates deterministic logic from code that can perform I/O.
Value semanticsAssignment behaves like an independent value, while ARC/COW keeps sharing efficient.
Typed absence and failureOption, Result, match, and ?= put uncertainty in the type flow.
Structured concurrencyScoped tasks, joins, timeouts, and channels keep concurrent work bounded.
Compile-time boundsFixed dimensions let the compiler prove safe indexing for arrays, vectors, and matrices.
Native performanceBlorp compiles to C while keeping performance work visible.
Tool-friendly designStable formatting and explicit effects make human and AI-written code easier to review.

Performance

Blorp compiles to C, so idiomatic Blorp code is intended to run within range of hand-written C. Below is a recent benchmark snapshot from the Blorp benchmark suite, run on an M4 MacBook Air. It's not meant to be authoritative, but shows broadly where blorp is positioned.

Benchmark	Blorp	C	Go	Python
numeric_loop	0.1242s	0.1215s (1.0x)	0.1726s (1.4x)	5.1754s (41.7x)
fib	0.1979s	0.1970s (1.0x)	0.2600s (1.3x)	7.6289s (38.5x)
string	0.1169s	0.1071s (0.9x)	0.1681s (1.4x)	0.1323s (1.1x)
array_sum	0.0011s	0.0005s (0.5x)	0.0045s (4.1x)	0.0957s (87.0x)
array_ops	0.0069s	0.0056s (0.8x)	0.0179s (2.6x)	0.4976s (72.1x)
dict_ops	0.1370s	-	0.1340s (1.0x)	0.3506s (2.6x)
list_ops	0.1236s	-	0.2074s (1.7x)	0.4296s (3.5x)
set_ops	0.2573s	-	0.5509s (2.1x)	0.2332s (0.9x)
threaded_cpu_map	0.0150s	0.0110s (0.7x)	0.0191s (1.3x)	0.9889s (65.9x)
channel_pipeline	0.0262s	0.0345s (1.3x)	0.0092s (0.4x)	0.1952s (7.5x)
sleep_fanout	0.0084s	0.0118s (1.4x)	0.0061s (0.7x)	0.0376s (4.5x)
options	0.0148s	-	-	-
simd	0.1302s	0.1071s (0.8x)	-	-
nbody	0.0539s	0.0495s (0.9x)	0.0489s (0.9x)	3.0480s (56.5x)
binary_trees	0.1217s	0.1125s (0.9x)	0.1158s (1.0x)	0.6813s (5.6x)
fannkuch	0.3254s	0.1819s (0.6x)	0.1493s (0.5x)	2.6348s (8.1x)
spectral_norm	0.0160s	0.0106s (0.7x)	0.0140s (0.9x)	0.9081s (56.8x)
mandelbrot	0.0020s	0.0021s (1.0x)	0.0195s (9.8x)	0.0590s (29.5x)
knucleotide	0.0231s	-	0.0153s (0.7x)	0.0601s (2.6x)
reverse_complement	0.0003s	-	0.0001s (0.3x)	0.0022s (7.3x)

Run details: in-process BENCH markers, 52 binaries compiled up front, 4 benchmark threads, Apple clang 21.0.0, Go 1.26.3, Python 3.14.4, and Python concurrency 3.14.4. Comparison cells show time plus the benchmark suite's reported factor relative to Blorp. A dash means that runner was not reported for that benchmark. See performance tools

Technical Details

Blorp is meant to feel direct at the surface while keeping the compiler's safety and runtime choices explicit.

Static TypesThe compiler checks imports, calls, match exhaustiveness, and fallible values before code reaches the C backend.
Hindley-Milner-Style InferenceLocal names usually do not need annotations; types flow from literals, calls, branches, and generic uses.
Value SemanticsAssignment and updates behave like independent values, while ARC and COW keep common sharing cheap.
Perceus OwnershipThe compiler lowers ownership with Perceus-style dup/drop and reuse analysis, then runtime reference counts preserve source semantics.
Native OutputTyped programs lower through Core IR to generated C, then a C compiler produces a native binary.