benchmarks

benches/cli_tool.cm

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+// cli_tool.cm — CLI tool simulation (macro benchmark)
+// Parse args + process data + transform + format output.
+// Simulates a realistic small utility program.
+
+var json = use('json')
+
+// Generate fake records
+function generate_records(n) {
+  var records = []
+  var x = 42
+  var i = 0
+  var status_vals = ["active", "inactive", "pending", "archived"]
+  var dept_vals = ["eng", "sales", "ops", "hr", "marketing"]
+  for (i = 0; i < n; i++) {
+    x = ((x * 1103515245 + 12345) & 0x7FFFFFFF) | 0
+    push(records, {
+      id: i + 1,
+      name: `user_${i}`,
+      score: (x % 1000) / 10,
+      status: status_vals[i % 4],
+      department: dept_vals[i % 5]
+    })
+  }
+  return records
+}
+
+// Filter records by field value
+function filter_records(records, field, value) {
+  var result = []
+  var i = 0
+  for (i = 0; i < length(records); i++) {
+    if (records[i][field] == value) {
+      push(result, records[i])
+    }
+  }
+  return result
+}
+
+// Group by a field
+function group_by(records, field) {
+  var groups = {}
+  var i = 0
+  var key = null
+  for (i = 0; i < length(records); i++) {
+    key = records[i][field]
+    if (!key) key = "unknown"
+    if (!groups[key]) groups[key] = []
+    push(groups[key], records[i])
+  }
+  return groups
+}
+
+// Aggregate: compute stats per group
+function aggregate(groups) {
+  var keys = array(groups)
+  var result = []
+  var i = 0
+  var j = 0
+  var grp = null
+  var total = 0
+  var mn = 0
+  var mx = 0
+  for (i = 0; i < length(keys); i++) {
+    grp = groups[keys[i]]
+    total = 0
+    mn = 999999
+    mx = 0
+    for (j = 0; j < length(grp); j++) {
+      total += grp[j].score
+      if (grp[j].score < mn) mn = grp[j].score
+      if (grp[j].score > mx) mx = grp[j].score
+    }
+    push(result, {
+      group: keys[i],
+      count: length(grp),
+      average: total / length(grp),
+      low: mn,
+      high: mx
+    })
+  }
+  return result
+}
+
+// Full pipeline: load → filter → sort → group → aggregate → encode
+function run_pipeline(n_records) {
+  // Generate data
+  var records = generate_records(n_records)
+
+  // Filter to active records
+  var filtered = filter_records(records, "status", "active")
+
+  // Sort by score
+  filtered = sort(filtered, "score")
+
+  // Limit to first 50
+  if (length(filtered) > 50) {
+    filtered = array(filtered, 0, 50)
+  }
+
+  // Group and aggregate
+  var groups = group_by(filtered, "department")
+  var stats = aggregate(groups)
+  stats = sort(stats, "average")
+
+  // Encode as JSON
+  var output = json.encode(stats)
+
+  return length(output)
+}
+
+return {
+  // Small dataset (100 records)
+  cli_pipeline_100: function(n) {
+    var i = 0
+    var x = 0
+    for (i = 0; i < n; i++) {
+      x += run_pipeline(100)
+    }
+    return x
+  },
+
+  // Medium dataset (1000 records)
+  cli_pipeline_1k: function(n) {
+    var i = 0
+    var x = 0
+    for (i = 0; i < n; i++) {
+      x += run_pipeline(1000)
+    }
+    return x
+  },
+
+  // Large dataset (10K records)
+  cli_pipeline_10k: function(n) {
+    var i = 0
+    var x = 0
+    for (i = 0; i < n; i++) {
+      x += run_pipeline(10000)
+    }
+    return x
+  }
+}