Fix lint errors in hash_pandas_object: noParameterAssign, useImportType, format

- Use local variable 'h' instead of reassigning 'hash' parameter in fnvString and fnvScalar
- Replace non-null assertion bytes[i]! with null-coalescing bytes[i] ?? 0
- Auto-fix: sort imports, make DataFrame import type-only, format test file

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: github-actions[bot]

src/stats/hash_pandas_object.ts

@@ -28,10 +28,10 @@
  * @module
  */
 
-import type { Scalar } from "../types.ts";
-import { DataFrame } from "../core/frame.ts";
-import { Series } from "../core/series.ts";
 import { Dtype } from "../core/dtype.ts";
+import type { DataFrame } from "../core/frame.ts";
+import { Series } from "../core/series.ts";
+import type { Scalar } from "../types.ts";
 
 // ─── FNV-1a 64-bit constants ──────────────────────────────────────────────────
 
@@ -46,21 +46,22 @@ function fnvByte(hash: bigint, byte: number): bigint {
 
 /** Hash an arbitrary string (UTF-8 bytes) into the FNV state. */
 function fnvString(hash: bigint, s: string): bigint {
+  let h = hash;
   for (let i = 0; i < s.length; i++) {
-    let code = s.charCodeAt(i);
+    const code = s.charCodeAt(i);
     // Encode as UTF-8 bytes
     if (code < 0x80) {
-      hash = fnvByte(hash, code);
+      h = fnvByte(h, code);
     } else if (code < 0x800) {
-      hash = fnvByte(hash, 0xc0 | (code >> 6));
-      hash = fnvByte(hash, 0x80 | (code & 0x3f));
+      h = fnvByte(h, 0xc0 | (code >> 6));
+      h = fnvByte(h, 0x80 | (code & 0x3f));
     } else {
-      hash = fnvByte(hash, 0xe0 | (code >> 12));
-      hash = fnvByte(hash, 0x80 | ((code >> 6) & 0x3f));
-      hash = fnvByte(hash, 0x80 | (code & 0x3f));
+      h = fnvByte(h, 0xe0 | (code >> 12));
+      h = fnvByte(h, 0x80 | ((code >> 6) & 0x3f));
+      h = fnvByte(h, 0x80 | (code & 0x3f));
     }
   }
-  return hash;
+  return h;
 }
 
 /** Hash a single scalar value into the FNV state. */
@@ -80,10 +81,11 @@ function fnvScalar(hash: bigint, val: Scalar): bigint {
     const buf = new ArrayBuffer(8);
     new DataView(buf).setFloat64(0, val, true);
     const bytes = new Uint8Array(buf);
+    let h = hash;
     for (let i = 0; i < 8; i++) {
-      hash = fnvByte(hash, bytes[i]!);
+      h = fnvByte(h, bytes[i] ?? 0);
     }
-    return hash;
+    return h;
   }
   if (typeof val === "bigint") {
     return fnvString(hash, val.toString());
@@ -128,10 +130,7 @@ export interface HashPandasObjectOptions {
  * h.iat(0) !== h.iat(1); // true  (with overwhelming probability)
  * ```
  */
-export function hashPandasObject(
-  obj: Series,
-  options?: HashPandasObjectOptions,
-): Series<number>;
+export function hashPandasObject(obj: Series, options?: HashPandasObjectOptions): Series<number>;
 
 /**
  * Return a `Series<number>` of FNV-1a 64-bit row-hashes for each row of `df`.
@@ -150,10 +149,7 @@ export function hashPandasObject(
  * // h.iat(0) is the hash of row 0; h.iat(1) is the hash of row 1
  * ```
  */
-export function hashPandasObject(
-  obj: DataFrame,
-  options?: HashPandasObjectOptions,
-): Series<number>;
+export function hashPandasObject(obj: DataFrame, options?: HashPandasObjectOptions): Series<number>;
 
 export function hashPandasObject(
   obj: Series | DataFrame,

tests/stats/hash_pandas_object.test.ts

@@ -106,18 +106,21 @@ describe("hashPandasObject — Series", () => {
 
   it("property: deterministic — same input same hash", () => {
     fc.assert(
-      fc.property(fc.array(fc.oneof(fc.integer(), fc.string(), fc.boolean()), { maxLength: 20 }), (arr) => {
-        const s1 = new Series({ data: arr });
-        const s2 = new Series({ data: arr });
-        const h1 = hashPandasObject(s1, { index: false });
-        const h2 = hashPandasObject(s2, { index: false });
-        for (let i = 0; i < arr.length; i++) {
-          if (h1.iat(i) !== h2.iat(i)) {
-            return false;
+      fc.property(
+        fc.array(fc.oneof(fc.integer(), fc.string(), fc.boolean()), { maxLength: 20 }),
+        (arr) => {
+          const s1 = new Series({ data: arr });
+          const s2 = new Series({ data: arr });
+          const h1 = hashPandasObject(s1, { index: false });
+          const h2 = hashPandasObject(s2, { index: false });
+          for (let i = 0; i < arr.length; i++) {
+            if (h1.iat(i) !== h2.iat(i)) {
+              return false;
+            }
           }
-        }
-        return true;
-      }),
+          return true;
+        },
+      ),
     );
   });
 });