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doc/getting_started/tutorials/04.reductions.ipynb

@@ -188,7 +188,7 @@
    "outputs": [],
    "source": [
     "def plot_meas(meas_np, meas, chunks):\n",
-    "    fig, ax = plt.subplots()\n",
+    "    _fig, ax = plt.subplots()\n",
     "\n",
     "    # Define the groups and bar width\n",
     "    groups = meas_np[\"time\"].keys()\n",

pyproject.toml

@@ -101,3 +101,6 @@ ignore = [
     "RET508",
     "SIM108",
 ]
+
+[tool.ruff.lint.extend-per-file-ignores]
+"tests/**" = ["F841"]

src/blosc2/core.py

@@ -1085,7 +1085,7 @@ def print_versions():
     for clib in sorted(clib_versions.keys()):
         print(f"  {clib}: {clib_versions[clib]}")
     print(f"Python version: {sys.version}")
-    (sysname, nodename, release, version, machine, processor) = platform.uname()
+    (sysname, _nodename, release, version, machine, processor) = platform.uname()
     print(f"Platform: {sysname}-{release}-{machine} ({version})")
     if sysname == "Linux":
         distro = os_release_pretty_name()

src/blosc2/lazyexpr.py

@@ -539,7 +539,7 @@ def fill_chunk_operands(
         if nchunk == 0:
             # Initialize the iterator for reading the chunks
             arr = operands["o0"]
-            chunks_idx, nchunks = get_chunks_idx(arr.shape, arr.chunks)
+            chunks_idx, _ = get_chunks_idx(arr.shape, arr.chunks)
             info = (reduc, aligned, low_mem, chunks_idx)
             iter_chunks = read_nchunk(list(operands.values()), info)
         # Run the asynchronous file reading function from a synchronous context
@@ -1162,7 +1162,7 @@ def chunked_eval(expression: str | Callable[[tuple, np.ndarray, tuple[int]], Non
         if where:
             # Make the where arguments part of the operands
             operands = {**operands, **where}
-        shape, _, _, fast_path = validate_inputs(operands, out)
+        _, _, _, fast_path = validate_inputs(operands, out)
 
         # Activate last read cache for NDField instances
         for op in operands:
@@ -1364,7 +1364,7 @@ def get_chunk(self, nchunk):
         shape = out.shape
         chunks = out.chunks
         # Calculate the shape of the (chunk) slice_ (specially at the end of the array)
-        chunks_idx, nchunks = get_chunks_idx(shape, chunks)
+        chunks_idx, _ = get_chunks_idx(shape, chunks)
         coords = tuple(np.unravel_index(nchunk, chunks_idx))
         slice_ = tuple(
             slice(c * s, min((c + 1) * s, shape[i]))