[Autoloop: perf-comparison]

benchmarks/pandas/bench_pd_array.py

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+"""
+Benchmark: pandas.array() — create and iterate typed arrays.
+Outputs JSON: {"function": "pd_array", "mean_ms": ..., "iterations": ..., "total_ms": ...}
+"""
+import json
+import time
+import pandas as pd
+import numpy as np
+
+SIZE = 10_000
+WARMUP = 5
+ITERATIONS = 100
+
+int_data = list(range(SIZE))
+float_data = [i * 0.5 for i in range(SIZE)]
+string_data = [f"item_{i % 100}" for i in range(SIZE)]
+mixed_data = [None if i % 3 == 0 else i for i in range(SIZE)]
+
+
+def run():
+    a = pd.array(int_data, dtype="Int64")
+    b = pd.array(float_data, dtype="Float64")
+    c = pd.array(string_data, dtype="string")
+    d = pd.array(mixed_data, dtype="Int64")
+
+    # Access elements
+    _ = a[-1]
+    _ = b[0]
+    _ = len(c)
+    _ = d[0]
+
+
+for _ in range(WARMUP):
+    run()
+
+start = time.perf_counter()
+for _ in range(ITERATIONS):
+    run()
+total_ms = (time.perf_counter() - start) * 1000
+
+print(
+    json.dumps(
+        {
+            "function": "pd_array",
+            "mean_ms": total_ms / ITERATIONS,
+            "iterations": ITERATIONS,
+            "total_ms": total_ms,
+        }
+    )
+)

benchmarks/pandas/bench_to_from_dict.py

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+"""
+Benchmark: DataFrame.to_dict / DataFrame.from_dict — dict orient conversions.
+Tests: list, records, split, index orient round-trips on a 10k-row DataFrame.
+Outputs JSON: {"function": "to_from_dict", "mean_ms": ..., "iterations": ..., "total_ms": ...}
+"""
+import time
+import json
+import pandas as pd
+
+SIZE = 10_000
+WARMUP = 5
+ITERATIONS = 50
+
+df = pd.DataFrame({
+    "a": list(range(SIZE)),
+    "b": [i * 1.5 for i in range(SIZE)],
+    "c": [f"str_{i % 100}" for i in range(SIZE)],
+})
+
+small_list = {"a": [1, 2, 3], "b": [4, 5, 6]}
+small_df = pd.DataFrame(small_list)
+small_index = {0: {"a": 1, "b": 4}, 1: {"a": 2, "b": 5}}
+
+for _ in range(WARMUP):
+    df.to_dict(orient="list")
+    df.to_dict(orient="records")
+    df.to_dict(orient="split")
+    df.to_dict(orient="index")
+    pd.DataFrame.from_dict(small_list)
+    pd.DataFrame.from_dict(small_index, orient="index")
+
+start = time.perf_counter()
+for _ in range(ITERATIONS):
+    df.to_dict(orient="list")
+    df.to_dict(orient="records")
+    df.to_dict(orient="split")
+    df.to_dict(orient="index")
+    pd.DataFrame.from_dict(small_list)
+    pd.DataFrame.from_dict(small_index, orient="index")
+total = (time.perf_counter() - start) * 1000
+
+print(json.dumps({
+    "function": "to_from_dict",
+    "mean_ms": round(total / ITERATIONS, 3),
+    "iterations": ITERATIONS,
+    "total_ms": round(total, 3),
+}))

benchmarks/tsb/bench_pd_array.ts

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+/**
+ * Benchmark: pdArray / PandasArray — create and iterate typed arrays.
+ * Outputs JSON: {"function": "pd_array", "mean_ms": ..., "iterations": ..., "total_ms": ...}
+ */
+import { pdArray } from "../../src/index.js";
+
+const SIZE = 10_000;
+const WARMUP = 5;
+const ITERATIONS = 100;
+
+const intData = Array.from({ length: SIZE }, (_, i) => i);
+const floatData = Array.from({ length: SIZE }, (_, i) => i * 0.5);
+const stringData = Array.from({ length: SIZE }, (_, i) => `item_${i % 100}`);
+const mixedData = Array.from({ length: SIZE }, (_, i) => (i % 3 === 0 ? null : i));
+
+function run(): void {
+  const a = pdArray(intData, "int64");
+  const b = pdArray(floatData, "float64");
+  const c = pdArray(stringData, "string");
+  const d = pdArray(mixedData);
+
+  // Access elements and iterate
+  void a.at(SIZE - 1);
+  void b.toArray();
+  void c.at(0);
+  void d.length;
+}
+
+for (let i = 0; i < WARMUP; i++) run();
+
+const start = performance.now();
+for (let i = 0; i < ITERATIONS; i++) run();
+const total = performance.now() - start;
+
+console.log(
+  JSON.stringify({
+    function: "pd_array",
+    mean_ms: total / ITERATIONS,
+    iterations: ITERATIONS,
+    total_ms: total,
+  }),
+);

benchmarks/tsb/bench_to_from_dict.ts

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+/**
+ * Benchmark: toDictOriented / fromDictOriented — DataFrame ↔ dict conversions.
+ * Tests all orient variants: "list", "records", "split", "index", "tight".
+ * Outputs JSON: {"function": "to_from_dict", "mean_ms": ..., "iterations": ..., "total_ms": ...}
+ */
+import { DataFrame, toDictOriented, fromDictOriented } from "../../src/index.js";
+
+const SIZE = 10_000;
+const WARMUP = 5;
+const ITERATIONS = 50;
+
+const df = new DataFrame({
+  a: Array.from({ length: SIZE }, (_, i) => i),
+  b: Array.from({ length: SIZE }, (_, i) => i * 1.5),
+  c: Array.from({ length: SIZE }, (_, i) => `str_${i % 100}`),
+});
+
+for (let i = 0; i < WARMUP; i++) {
+  toDictOriented(df, "list");
+  toDictOriented(df, "records");
+  toDictOriented(df, "split");
+  toDictOriented(df, "index");
+  toDictOriented(df, "tight");
+  fromDictOriented({ a: [1, 2, 3], b: [4, 5, 6] });
+  fromDictOriented({ 0: { a: 1, b: 4 }, 1: { a: 2, b: 5 } }, "index");
+}
+
+const start = performance.now();
+for (let i = 0; i < ITERATIONS; i++) {
+  toDictOriented(df, "list");
+  toDictOriented(df, "records");
+  toDictOriented(df, "split");
+  toDictOriented(df, "index");
+  toDictOriented(df, "tight");
+  fromDictOriented({ a: [1, 2, 3], b: [4, 5, 6] });
+  fromDictOriented({ 0: { a: 1, b: 4 }, 1: { a: 2, b: 5 } }, "index");
+}
+const total = performance.now() - start;
+
+console.log(
+  JSON.stringify({
+    function: "to_from_dict",
+    mean_ms: Math.round((total / ITERATIONS) * 1000) / 1000,
+    iterations: ITERATIONS,
+    total_ms: Math.round(total * 1000) / 1000,
+  }),
+);