meta-ast 0.4.0

Polyglot static-analysis engine: extract symbols and cross-language dependency graphs from 8 supported source languages, with optional MetaCall deployment manifest generation.
Documentation
<div align="center">
  <img src="docs/assets/metast.png" alt="meta-ast Logo" width="400">
  <p align="center"><strong>Standalone static analysis and dependency graph generator for polyglot source trees</strong></p>
</div>

---

`meta-ast` is a fast, standalone static analysis engine that parses multi-language projects, builds symbol-level dependency graphs, detects cyclic imports, and generates MetaCall deployment manifests. Written in Rust, powered by tree-sitter, with no runtime execution of user code.

Built as part of **Google Summer of Code 2026** for the **MetaCall** organization by **[Khaled Alam](https://github.com/k5602)**.

Supports **8 languages**: Python, JavaScript, TypeScript, TSX, C, C++, Rust, Go.

---

## Quick start

```bash
# Requires Rust toolchain - https://rustup.rs
git clone https://github.com/metacall/meta-ast.git
cd meta-ast
cargo build --release
```

The binary is at `./target/release/meta-ast`.

---

## Installation

### From crates.io (recommended)

`meta-ast` is published to [crates.io](https://crates.io/crates/meta-ast). With a
Rust toolchain installed, install the latest release in one command:

```bash
cargo install meta-ast
```

This installs the core analyzer (`inspect` and `graph` subcommands). To also
enable the MetaCall deployment manifest generator (`deploy` subcommand), install
with the `metacall-deploy` feature:

```bash
cargo install meta-ast --features metacall-deploy
```

The binary lands at `~/.cargo/bin/meta-ast` (on your `PATH` if cargo's bin dir is
configured). No external services, network calls, or runtime execution of your
code are involved.

### From source

```bash
git clone https://github.com/metacall/meta-ast.git
cd meta-ast
cargo build --release                 # core only
# or, with the deploy module:
cargo build --release --features metacall-deploy
```

The binary is at `./target/release/meta-ast`.

---

## Goals

`meta-ast` exists to give polyglot codebases a single, fast, language-agnostic
view of their structure without executing any user code. Its objectives:

- **Parse 8 languages with one tool.** Python, JavaScript, TypeScript, TSX, C,
  C++, Rust, and Go flow through a uniform tree-sitter pipeline. A mixed
  Python/JS/Rust project is one graph, not three glued together.
- **Normalize to a stable IR.** Every declaration becomes a `Symbol` with a
  consistent shape and a stable JSON/YAML output contract. Downstream tooling
  consumes results without caring about the source language.
- **Surface deployment structure.** Cross-file dependency graphs plus Tarjan
  SCC reveal cyclic import clusters and independent units. These feed the
  MetaCall Function Mesh deployment model via pod-based manifests.
- **Recover, never abort.** Partial or malformed trees are parsed as far as
  possible and any parse/extraction gaps are accumulated as diagnostics. A
  broken file never takes down the whole analysis.
- **Stay standalone and safe.** No runtime execution of target code, no network,
  no external services. Pure static analysis driven by CLI or library API.

---

## Scope

**In scope:**

- Syntactic symbol extraction (functions, classes, objects, methods, structs,
  enums, interfaces, namespaces) and their visibility/doc metadata.
- Cross-file import resolution, reference resolution, and dependency graph
  assembly with confidence-weighted edges.
- Cyclic-import detection (Tarjan SCC) and deployment-unit classification.
- MetaCall pod-based deployment manifest generation (`metacall.pods.json`) and
  Function Mesh annotation (`metacall.mesh.json`) behind the `metacall-deploy`
  feature.
- External dependency resolution: per-language lockfile/manifest parsing to
  pin dependencies with exact versions.
- Single-snapshot analysis of a directory tree via CLI or `analyze_graph`.

---

## Use cases

- **Architecture review & onboarding.** Get a normalized map of every symbol and
  its dependencies across a polyglot repo to understand structure quickly.
  Run `meta-ast inspect` on a checkout and read the JSON/YAML, or open the
  interactive dashboard from `meta-ast graph --html`.
- **Cyclic dependency guard.** Run `meta-ast graph` in CI to fail builds that
  introduce accidental import cycles (Tarjan SCC flags cyclic clusters).
- **Dependency-graph diffing & refactors.** Before splitting a module or
  deleting a package, generate the graph and confirm what actually depends on
  it across languages - catch hidden cross-language coupling a grep would miss.
- **Pre-commit / code-review signal.** Emit the graph or inspect output as a
  PR artifact so reviewers see structural impact (new symbols, new edges) rather
  than reading diffs blind.
- **Deployment planning for MetaCall / Function Mesh.** With the `metacall-deploy`
  feature, the `deploy` subcommand turns detected cross-language
  `metacall_load_from_*` call sites and SCC units into manifests that drive
  co-deployment vs. independent-function decisions. Requires the feature-enabled
  install (`cargo install meta-ast --features metacall-deploy`).
- **Documentation & visualization.** Emit an interactive Cytoscape.js dashboard
  (`--html`, loaded from a CDN and cached by the browser) to explore ownership,
  references, and deployment units visually.
- **Library integration.** Consume `meta-ast` as a crate: `analyze_graph`
  returns a `GraphAnalysis` (`CodeGraph` + `SccAnalysis`) for custom tooling,
  linters, or report generators.

---

## Subcommands

### `inspect`

Extracts all function, class, and object declarations from a codebase.

```bash
meta-ast inspect <path> [-l language] [-f json|yaml] [-o output.json]
```

### `graph`

Builds the cross-file dependency graph, resolves imports, and runs Tarjan SCC to identify cyclic clusters and independent deployment units.

```bash
meta-ast graph <path> [-l language] [-f json|yaml] [-o graph.json]
meta-ast graph <path> --html                    # interactive Cytoscape.js dashboard (CDN, browser-cached)
meta-ast graph <path> --datagraph               # export detailed datagraph.json (requires --features dataflow)
meta-ast graph <path> --watch                   # watch mode: continuous re-analysis on file changes (requires --features watch)
meta-ast graph <path> --watch --watch-debounce 100 --html -o graph.html
```

`--watch` enters a debounced watch loop: on each file change, only changed files
are re-extracted using BLAKE3 cryptographic content fingerprinting (unchanged files reuse cached `Arc` extractions), then the graph + SCC
are rebuilt. Snapshot IDs increment with each re-analysis tick. Requires
`cargo install meta-ast --features watch` (or `cargo build --features watch`).

### `deploy` *(requires `--features metacall-deploy`)*

Scans for cross-language `metacall_load_from_*` call sites, resolves external dependencies from lockfiles and package manifests, partitions files into same-language pods, and generates deployment artifacts.

```bash
cargo build --release --features metacall-deploy

meta-ast deploy <path> [-f json|yaml] [-o ./out] # generate manifests
meta-ast deploy <path> --check                  # CI validation: verify every cut edge has an RPC stub
```

Generates two artifacts:

| File | Description |
|---|---|
| `metacall.pods.json` | Pod manifest: language-based deployment units, inter-pod edges with confidence scores, per-pod dependency lists with pinned versions, and AST node metrics |
| `metacall.mesh.json` | SCC-derived Function Mesh topology annotation with cross-language call-site attribution |

See [docs/DEPLOY.md](docs/DEPLOY.md) for scanner details, confidence scoring, pod partitioning, manifest schema, and the fairness check used in CI.

---

## Documentation

| Document | Description |
|---|---|
| [CONTRIBUTING.md]CONTRIBUTING.md | How to build, test, and submit changes |
| [docs/ARCHITECTURE.md]docs/ARCHITECTURE.md | High-level pipeline and component boundaries |
| [docs/STRUCTURE.md]docs/STRUCTURE.md | Module layout, data structures, design patterns |
| [docs/DEPLOY.md]docs/DEPLOY.md | Deploy module: scanner, manifests, mesh annotation |
| [docs/ROADMAP.md]docs/ROADMAP.md | Phase-by-phase delivery plan |
| [docs/adr/]docs/adr/ | Architecture Decision Records |
| [docs/rfcs/]docs/rfcs/ | Design RFCs |
| [docs/specs/]docs/specs/ | Requirements and traceability |

---

## Roadmap

- **Phase 4 (In Progress)**: Watch mode complete (feature-gated behind `--features watch`).
  Remaining: C ABI scaffolding.
- **Phase 5 (Complete)**: `metacall-deploy` - call-site scanning, pod partitioning, dependency resolution, pod manifests, Function Mesh annotation, fairness checking.
- **Phase 6 (Planned)**: Language expansion (C#, Java).

Full details in [docs/ROADMAP.md](docs/ROADMAP.md).

---

## Benchmarking

Performance is measured with [criterion](https://github.com/japaric/criterion.rs)
via three benchmark suites (`harness = false`):

- `benches/pipeline.rs` - end-to-end extraction across the per-language fixtures
  (python, javascript, typescript, tsx, rust, go, c, cpp, mixed).
- `benches/graph.rs` - graph construction, Tarjan SCC on varied topologies
  (acyclic chains, single/multiple cycles, dense graphs), edge deduplication,
  and node lookup at scale (up to 10k nodes / 10k duplicates).
- `benches/incremental.rs` - cold vs warm incremental re-analysis after file modifications
  (requires `--features watch`).

Run them locally:

```bash
cargo bench                                    # all suites
cargo bench --bench pipeline                   # extraction only
cargo bench --bench graph -- --plotting-backend=plotters
cargo bench --bench incremental --features watch # incremental watch benchmark
```

Benchmarks run on the fixture corpus under `tests/fixtures/`, so results scale
with that corpus. Typical wall-clock figures (your hardware will vary):

- Per-language extraction of the fixture set completes in low milliseconds.
- SCC and node lookup stay sub-millisecond into the thousands-of-nodes range;
  edge deduplication is linear in the duplicate count.

For reproducible CI numbers, pin the toolchain (MSRV 1.94.0) and run on a
quiet machine; criterion reports mean/stddev and supports `--save-baseline` for
regression tracking.

---

## License

Apache License, Version 2.0. See `LICENSE` for details.