feat(ci): add codec perf/CI gates

.github/workflows/ci.yml

@@ -159,7 +159,12 @@ jobs:
         run: python test/python/library_integration.py --suite all
 
   codec-suite:
-    if: github.event_name == 'schedule' || github.event_name == 'workflow_dispatch'
+    if: >-
+      github.event_name == 'schedule' ||
+      github.event_name == 'workflow_dispatch' ||
+      github.event_name == 'push' ||
+      (github.event_name == 'pull_request' &&
+        contains(github.event.pull_request.labels.*.name, 'area:codec'))
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4

docs/configuration.md

@@ -301,6 +301,12 @@ export TYWRAP_TORCH_ALLOW_COPY="1"
 # Performance tuning
 export TYWRAP_CACHE_DIR="./.tywrap/cache"
 export TYWRAP_MEMORY_LIMIT="1024"
+export TYWRAP_PERF_BUDGETS="1"
+export TYWRAP_PERF_TIME_BUDGET_MS="2000"
+export TYWRAP_PERF_MEMORY_BUDGET_MB="64"
+export TYWRAP_CODEC_PERF_ITERATIONS="200"
+export TYWRAP_CODEC_PERF_TIME_BUDGET_MS="500"
+export TYWRAP_CODEC_PERF_MEMORY_BUDGET_MB="32"
 
 # Development
 export TYWRAP_VERBOSE="true"

test/codec-performance.test.ts

@@ -0,0 +1,85 @@
+import { describe, it, expect } from 'vitest';
+import { decodeValue } from '../src/utils/codec.js';
+import { isNodejs } from '../src/utils/runtime.js';
+
+const shouldRun = isNodejs() && (process.env.CI || process.env.TYWRAP_PERF_BUDGETS === '1');
+const describeBudget = shouldRun ? describe : describe.skip;
+
+const readEnvNumber = (name: string, fallback: string): number =>
+  Number(process.env[name] ?? fallback);
+
+const runGc = (): void => {
+  if (global.gc) {
+    global.gc();
+  }
+};
+
+describeBudget('Codec performance budgets', () => {
+  it('decodes representative envelopes within time/memory budgets', () => {
+    const iterations = readEnvNumber('TYWRAP_CODEC_PERF_ITERATIONS', '200');
+    const timeBudgetMs = readEnvNumber('TYWRAP_CODEC_PERF_TIME_BUDGET_MS', '500');
+    const memoryBudgetMb = readEnvNumber('TYWRAP_CODEC_PERF_MEMORY_BUDGET_MB', '32');
+    const memoryBudgetBytes = memoryBudgetMb * 1024 * 1024;
+
+    const sparseEnvelope = {
+      __tywrap__: 'scipy.sparse',
+      codecVersion: 1,
+      encoding: 'json',
+      format: 'csr',
+      shape: [100, 100],
+      data: Array.from({ length: 200 }, (_, idx) => idx % 7),
+      indices: Array.from({ length: 200 }, (_, idx) => idx % 100),
+      indptr: Array.from({ length: 101 }, (_, idx) => Math.min(idx * 2, 200)),
+    } as const;
+
+    const torchEnvelope = {
+      __tywrap__: 'torch.tensor',
+      codecVersion: 1,
+      encoding: 'ndarray',
+      value: {
+        __tywrap__: 'ndarray',
+        codecVersion: 1,
+        encoding: 'json',
+        data: [
+          [1, 2],
+          [3, 4],
+        ],
+        shape: [2, 2],
+      },
+      shape: [2, 2],
+      dtype: 'float32',
+      device: 'cpu',
+    } as const;
+
+    const sklearnEnvelope = {
+      __tywrap__: 'sklearn.estimator',
+      codecVersion: 1,
+      encoding: 'json',
+      className: 'LinearRegression',
+      module: 'sklearn.linear_model._base',
+      version: '1.4.2',
+      params: {
+        fit_intercept: true,
+        copy_X: true,
+      },
+    } as const;
+
+    runGc();
+    const startMem = process.memoryUsage().heapUsed;
+    const start = performance.now();
+
+    for (let i = 0; i < iterations; i += 1) {
+      decodeValue(sparseEnvelope);
+      decodeValue(torchEnvelope);
+      decodeValue(sklearnEnvelope);
+    }
+
+    const duration = performance.now() - start;
+    runGc();
+    const endMem = process.memoryUsage().heapUsed;
+    const deltaMem = endMem - startMem;
+
+    expect(duration).toBeLessThan(timeBudgetMs);
+    expect(deltaMem).toBeLessThan(memoryBudgetBytes);
+  });
+});