fn discount(price: Int) -> Int
    requires price >= 0
    ensures result >= 0
{
    return price - 10
}

error[E700] promise cannot be kept: 'discount' ensures result >= 0
  proven without running the program: price = 5 gives result = -5

That ensures is not a comment or a runtime assert. The Z3 theorem prover verifies it for every possible input before execution — and refutes it with an exact counterexample when it lies.

Why Velaris

Why floats are proven in IEEE-754 rather than as real numbers, and what that costs: docs/floats.md.

Loops without written invariants are handled where the boring invariants suffice: the compiler proposes bounds on each counter and keeps the ones a loop step cannot break (see examples/inferred.vel). Anything richer — membership, sortedness — still needs an invariant line.

The prover never claims "proven without running" unless the counterexample is premise-complete — untranslatable assumptions abandon the proof to runtime checks rather than risk a false alarm. Soundness reports are treated as security issues.

Install

pip install velaris-lang
velaris doctor
velaris new hello && cd hello && velaris main.vel

Standalone executable (no Python required) — download for Windows / Linux / macOS from the latest release, then:

velaris doctor

With Python 3.10+:

pip install velaris-lang
velaris new hello && cd hello && velaris main.vel

Zero install — the playground runs the real compiler in your browser.

Optional extras for source installs: pip install ".[full]" adds z3-solver (compile-time proofs) and llvmlite (native speed); without them, promises are checked at runtime and everything runs interpreted — same language, honestly degraded.

Everyday ergonomics

keep_if(xs, fn(n: Int) -> Bool { return n % 2 == 0 })   // inline functions
format("hi {}, {} left", name, count)                    // text with holes
args()                                                   // command line
post(url, body) / fetch_status(url)                      // not just GET

Function values are lifted to real functions, so proofs and native compilation apply to them unchanged — and they can carry their own requires / ensures, proven like any other function's. They can't capture surrounding variables — the compiler tells you to pass them in instead.

Two real programs

examples/ledger.vel — an expense tracker: records, integer cents, file persistence, sorted reports. examples/wordcount.vel — text analysis: velaris examples/wordcount.vel <file> [n] counts word frequencies and prints a ranked histogram. examples/fetcher.vel — an HTTP tool: checks a status, then summarises a page, with every network call declared and every failure handled.

JSON

json_get(doc, "user.name")    json_int(doc, "user.age")
json_len(doc, "tags")         json_of(Person(name: "gowri", age: 30))

Paths walk objects and lists, every read can fail (a missing field is a possibility, not a crash), and none of it is an effect — parsing text is pure.

Reaching other languages

fn today() -> Text uses ffi or fail {
    let nothing: List of Text = []
    return try py("datetime.date", "today", nothing)
}

py / py_int / py_float / py_json call Python functions, and py_new / py_do / py_field / py_close hold real objects — a database connection, a session — so every library Python has is reachable — but only from a function that declares uses ffi, and it can fail like anything else that leaves your program.

Libraries

velaris add https://example.com/geo.vel as geo   # vendored into lib/
velaris deps                                     # what you depend on
velaris verify                                   # unchanged since?

A library is compiled before it is accepted, recorded with its exact sha256 in velaris.toml, and kept in your repository where you can read it. No registry, no resolver, nothing fetched at build time.

Imports

import "lib/geo.vel" as geo      // named: geo.distance(a, b)
import "std.vel"                 // flat: sort(xs)

A named import prefixes that library's functions, so two libraries that both export distance can be used in the same file.

Tooling

velaris trace program.vel (watch every call as it happens) · velaris test program.vel (runs every test_* function written in Velaris) · velaris check program.vel (compile without running; several files at once, --json for tools) · velaris explain program.vel (a walkthrough of every function: effects, promises, and whether they are proven — explain <folder> maps a whole project) · velaris repl (definitions are proof-checked as you type them) · velaris fmt (canonical style, --check for CI) · velaris lsp (errors as you type in any LSP editor; a VS Code extension lives in editor/vscode) · velaris doctor · velaris new · --json errors for automation.

Standard library

Written in Velaris, in stdlib/std.vel — and it keeps its own promises: sort carries ensures is_sorted(result), max_of requires a nonempty list, and violating a library requires is a compile error at your call site. Full reference, generated from the real compiler.

Numbers

Whole numbers are 64-bit. Arithmetic that outgrows that range is an error, not a silent wrap — and the same error whether your code is interpreted or running as machine code. Floats are IEEE-754 doubles, proven as such.

Stability

Semantic versioning: breaking changes only at major versions (v2.0 migrated the fallible builtins, compiler-guided). CI tests every push on Linux and Windows, Python 3.10 and 3.12, with and without the optional dependencies. Errors are stable, numbered, and fully documented.

Contributing

The entire implementation is one readable file, velaris.py, in pipeline order — lexer to LSP. Start with CONTRIBUTING.md; 52 example programs in examples/ each carry an expected verdict (half are designed to be rejected — each rejection demonstrates a guarantee).

License

MIT © Gowri Shankar