Ruff: b905 (strict zip) (#29336)

* added mutable default args

* most of the Bs

* add comment about lrucache

* b905
old-commit-hash: e4ead4f183

pyproject.toml

@@ -198,7 +198,7 @@ build-backend = "poetry.core.masonry.api"
 # https://beta.ruff.rs/docs/configuration/#using-pyprojecttoml
 [tool.ruff]
 select = ["E", "F", "W", "PIE", "C4", "ISC", "RUF100", "A", "B"]
-ignore = ["W292", "E741", "E402", "C408", "ISC003", "B027", "B024", "B905"]
+ignore = ["W292", "E741", "E402", "C408", "ISC003", "B027", "B024"]
 line-length = 160
 target-version="py311"
 exclude = [

selfdrive/car/chrysler/radar_interface.py

@@ -25,7 +25,7 @@ def _create_radar_can_parser(car_fingerprint):
   messages = list(zip(RADAR_MSGS_C +
                       RADAR_MSGS_D,
                       [20] * msg_n +  # 20Hz (0.05s)
-                      [20] * msg_n))  # 20Hz (0.05s)
+                      [20] * msg_n, strict=True))  # 20Hz (0.05s)
 
   return CANParser(DBC[car_fingerprint]['radar'], messages, 1)
 

selfdrive/car/ford/radar_interface.py

@@ -15,7 +15,7 @@ DELPHI_MRR_RADAR_MSG_COUNT = 64
 
 def _create_delphi_esr_radar_can_parser(CP) -> CANParser:
   msg_n = len(DELPHI_ESR_RADAR_MSGS)
-  messages = list(zip(DELPHI_ESR_RADAR_MSGS, [20] * msg_n))
+  messages = list(zip(DELPHI_ESR_RADAR_MSGS, [20] * msg_n, strict=True))
 
   return CANParser(RADAR.DELPHI_ESR, messages, CanBus(CP).radar)
 

selfdrive/car/gm/radar_interface.py

@@ -25,7 +25,7 @@ def create_radar_can_parser(car_fingerprint):
                      ['TrkRange'] * NUM_SLOTS + ['TrkRangeRate'] * NUM_SLOTS +
                      ['TrkRangeAccel'] * NUM_SLOTS + ['TrkAzimuth'] * NUM_SLOTS +
                      ['TrkWidth'] * NUM_SLOTS + ['TrkObjectID'] * NUM_SLOTS,
-                     [RADAR_HEADER_MSG] * 7 + radar_targets * 6))
+                     [RADAR_HEADER_MSG] * 7 + radar_targets * 6, strict=True))
 
   messages = list({(s[1], 14) for s in signals})
 

selfdrive/car/toyota/radar_interface.py

@@ -15,7 +15,7 @@ def _create_radar_can_parser(car_fingerprint):
 
   msg_a_n = len(RADAR_A_MSGS)
   msg_b_n = len(RADAR_B_MSGS)
-  messages = list(zip(RADAR_A_MSGS + RADAR_B_MSGS, [20] * (msg_a_n + msg_b_n)))
+  messages = list(zip(RADAR_A_MSGS + RADAR_B_MSGS, [20] * (msg_a_n + msg_b_n), strict=True))
 
   return CANParser(DBC[car_fingerprint]['radar'], messages, 1)
 

selfdrive/debug/filter_log_message.py

@@ -59,7 +59,7 @@ if __name__ == "__main__":
       logs = [args.route[0]]
     else:
       r = Route(args.route[0])
-      logs = [q_log if r_log is None else r_log for (q_log, r_log) in zip(r.qlog_paths(), r.log_paths())]
+      logs = [q_log if r_log is None else r_log for (q_log, r_log) in zip(r.qlog_paths(), r.log_paths(), strict=True)]
 
   if len(args.route) == 2 and logs:
     n = int(args.route[1])

selfdrive/debug/internal/qlog_size.py

@@ -27,7 +27,7 @@ def make_pie(msgs, typ):
   sizes_large = [(k, sz) for (k, sz) in sizes if sz >= total * MIN_SIZE / 100]
   sizes_large += [('other', sum(sz for (_, sz) in sizes if sz < total * MIN_SIZE / 100))]
 
-  labels, sizes = zip(*sizes_large)
+  labels, sizes = zip(*sizes_large, strict=True)
 
   plt.figure()
   plt.title(f"{typ}")

selfdrive/locationd/models/loc_kf.py

@@ -191,9 +191,9 @@ class LocKalman():
 
     # Observation matrix modifier
     H_mod_sym = sp.Matrix(np.zeros((dim_state, dim_state_err)))
-    for p_idx, p_err_idx in zip(p_idxs, p_err_idxs):
+    for p_idx, p_err_idx in zip(p_idxs, p_err_idxs, strict=True):
       H_mod_sym[p_idx[0]:p_idx[1], p_err_idx[0]:p_err_idx[1]] = np.eye(p_idx[1] - p_idx[0])
-    for q_idx, q_err_idx in zip(q_idxs, q_err_idxs):
+    for q_idx, q_err_idx in zip(q_idxs, q_err_idxs, strict=True):
       H_mod_sym[q_idx[0]:q_idx[1], q_err_idx[0]:q_err_idx[1]] = 0.5 * quat_matrix_r(state[q_idx[0]:q_idx[1]])[:, 1:]
 
     # these error functions are defined so that say there
@@ -205,17 +205,17 @@ class LocKalman():
     delta_x = sp.MatrixSymbol('delta_x', dim_state_err, 1)
 
     err_function_sym = sp.Matrix(np.zeros((dim_state, 1)))
-    for q_idx, q_err_idx in zip(q_idxs, q_err_idxs):
+    for q_idx, q_err_idx in zip(q_idxs, q_err_idxs, strict=True):
       delta_quat = sp.Matrix(np.ones(4))
       delta_quat[1:, :] = sp.Matrix(0.5 * delta_x[q_err_idx[0]: q_err_idx[1], :])
       err_function_sym[q_idx[0]:q_idx[1], 0] = quat_matrix_r(nom_x[q_idx[0]:q_idx[1], 0]) * delta_quat
-    for p_idx, p_err_idx in zip(p_idxs, p_err_idxs):
+    for p_idx, p_err_idx in zip(p_idxs, p_err_idxs, strict=True):
       err_function_sym[p_idx[0]:p_idx[1], :] = sp.Matrix(nom_x[p_idx[0]:p_idx[1], :] + delta_x[p_err_idx[0]:p_err_idx[1], :])
 
     inv_err_function_sym = sp.Matrix(np.zeros((dim_state_err, 1)))
-    for p_idx, p_err_idx in zip(p_idxs, p_err_idxs):
+    for p_idx, p_err_idx in zip(p_idxs, p_err_idxs, strict=True):
       inv_err_function_sym[p_err_idx[0]:p_err_idx[1], 0] = sp.Matrix(-nom_x[p_idx[0]:p_idx[1], 0] + true_x[p_idx[0]:p_idx[1], 0])
-    for q_idx, q_err_idx in zip(q_idxs, q_err_idxs):
+    for q_idx, q_err_idx in zip(q_idxs, q_err_idxs, strict=True):
       delta_quat = quat_matrix_r(nom_x[q_idx[0]:q_idx[1], 0]).T * true_x[q_idx[0]:q_idx[1], 0]
       inv_err_function_sym[q_err_idx[0]:q_err_idx[1], 0] = sp.Matrix(2 * delta_quat[1:])
 

selfdrive/locationd/test/test_laikad.py

@@ -173,7 +173,7 @@ class TestLaikad(unittest.TestCase):
     self.assertTrue(kf_valid)
 
   def test_laika_online_nav_only(self):
-    for use_qcom, logs in zip([True, False], [self.logs_qcom, self.logs]):
+    for use_qcom, logs in zip([True, False], [self.logs_qcom, self.logs], strict=True):
       laikad = Laikad(auto_update=True, valid_ephem_types=EphemerisType.NAV, use_qcom=use_qcom)
       # Disable fetch_orbits to test NAV only
       correct_msgs = verify_messages(logs, laikad)
@@ -215,7 +215,7 @@ class TestLaikad(unittest.TestCase):
 
   def test_get_navs_in_process(self):
     for auto_fetch_navs in [True, False]:
-      for use_qcom, logs in zip([True, False], [self.logs_qcom, self.logs]):
+      for use_qcom, logs in zip([True, False], [self.logs_qcom, self.logs], strict=True):
         laikad = Laikad(auto_update=False, use_qcom=use_qcom, auto_fetch_navs=auto_fetch_navs)
         has_navs = False
         has_fix = False
@@ -248,7 +248,7 @@ class TestLaikad(unittest.TestCase):
 
   def test_cache(self):
     use_qcom = True
-    for use_qcom, logs in zip([True, False], [self.logs_qcom, self.logs]):
+    for use_qcom, logs in zip([True, False], [self.logs_qcom, self.logs], strict=True):
       Params().remove(EPHEMERIS_CACHE)
       laikad = Laikad(auto_update=True, save_ephemeris=True, use_qcom=use_qcom)
       def wait_for_cache():

selfdrive/locationd/torqued.py

@@ -63,7 +63,7 @@ class PointBuckets:
   def __init__(self, x_bounds, min_points, min_points_total):
     self.x_bounds = x_bounds
     self.buckets = {bounds: NPQueue(maxlen=POINTS_PER_BUCKET, rowsize=3) for bounds in x_bounds}
-    self.buckets_min_points = dict(zip(x_bounds, min_points))
+    self.buckets_min_points = dict(zip(x_bounds, min_points, strict=True))
     self.min_points_total = min_points_total
 
   def bucket_lengths(self):
@@ -73,7 +73,8 @@ class PointBuckets:
     return sum(self.bucket_lengths())
 
   def is_valid(self):
-    return all(len(v) >= min_pts for v, min_pts in zip(self.buckets.values(), self.buckets_min_points.values())) and (self.__len__() >= self.min_points_total)
+    return all(len(v) >= min_pts for v, min_pts in zip(self.buckets.values(), self.buckets_min_points.values(), strict=True)) \
+                                                                                and (self.__len__() >= self.min_points_total)
 
   def add_point(self, x, y):
     for bound_min, bound_max in self.x_bounds:

selfdrive/modeld/runners/onnx_runner.py

@@ -36,16 +36,16 @@ def run_loop(m, tf8_input=False):
 
   # run once to initialize CUDA provider
   if "CUDAExecutionProvider" in m.get_providers():
-    m.run(None, dict(zip(keys, [np.zeros(shp, dtype=itp) for shp, itp in zip(ishapes, itypes)])))
+    m.run(None, dict(zip(keys, [np.zeros(shp, dtype=itp) for shp, itp in zip(ishapes, itypes, strict=True)], strict=True)))
 
   print("ready to run onnx model", keys, ishapes, file=sys.stderr)
   while 1:
     inputs = []
-    for k, shp, itp in zip(keys, ishapes, itypes):
+    for k, shp, itp in zip(keys, ishapes, itypes, strict=True):
       ts = np.product(shp)
       #print("reshaping %s with offset %d" % (str(shp), offset), file=sys.stderr)
       inputs.append(read(ts, (k=='input_img' and tf8_input)).reshape(shp).astype(itp))
-    ret = m.run(None, dict(zip(keys, inputs)))
+    ret = m.run(None, dict(zip(keys, inputs, strict=True)))
     #print(ret, file=sys.stderr)
     for r in ret:
       write(r.astype(np.float32))

selfdrive/test/process_replay/compare_logs.py

@@ -70,7 +70,7 @@ def compare_logs(log1, log2, ignore_fields=None, ignore_msgs=None, tolerance=Non
     raise Exception(f"logs are not same length: {len(log1)} VS {len(log2)}\n\t\t{cnt1}\n\t\t{cnt2}")
 
   diff = []
-  for msg1, msg2 in zip(log1, log2):
+  for msg1, msg2 in zip(log1, log2, strict=True):
     if msg1.which() != msg2.which():
       raise Exception("msgs not aligned between logs")
 

selfdrive/test/process_replay/test_debayer.py

@@ -137,7 +137,7 @@ if __name__ == "__main__":
         failed = True
         diff += 'amount of frames not equal\n'
 
-      for i, (frame, cmp_frame) in enumerate(zip(frames, cmp_frames)):
+      for i, (frame, cmp_frame) in enumerate(zip(frames, cmp_frames, strict=True)):
         for j in range(3):
           fr = frame[j]
           cmp_f = cmp_frame[j]
@@ -159,7 +159,7 @@ if __name__ == "__main__":
               diff += f'different at a large amount of pixels ({diff_len})\n'
             else:
               diff += 'different at (frame, yuv, pixel, ref, HEAD):\n'
-              for k in zip(*np.nonzero(frame_diff)):
+              for k in zip(*np.nonzero(frame_diff), strict=True):
                 diff += f'{i}, {yuv_i[j]}, {k}, {cmp_f[k]}, {fr[k]}\n'
 
       if failed:

selfdrive/test/update_ci_routes.py

@@ -52,7 +52,7 @@ def sync_to_ci_public(route):
     return True
 
   print(f"Uploading {route}")
-  for (source_account, source_bucket), source_key in zip(SOURCES, source_keys):
+  for (source_account, source_bucket), source_key in zip(SOURCES, source_keys, strict=True):
     print(f"Trying {source_account}/{source_bucket}")
     cmd = [
       "azcopy",

selfdrive/tombstoned.py

@@ -54,7 +54,7 @@ def get_tombstones():
       with os.scandir(folder) as d:
 
         # Loop over first 1000 directory entries
-        for _, f in zip(range(1000), d):
+        for _, f in zip(range(1000), d, strict=False):
           if f.name.startswith("tombstone"):
             files.append((f.path, int(f.stat().st_ctime)))
           elif f.name.endswith(".crash") and f.stat().st_mode == 0o100640:

system/hardware/tici/tests/compare_casync_manifest.py

@@ -40,7 +40,7 @@ if __name__ == "__main__":
   # Get content-length for each chunk
   with multiprocessing.Pool() as pool:
     szs = list(tqdm(pool.imap(get_chunk_download_size, to), total=len(to)))
-  chunk_sizes = {t.sha: sz for (t, sz) in zip(to, szs)}
+  chunk_sizes = {t.sha: sz for (t, sz) in zip(to, szs, strict=True)}
 
   sources: Dict[str, List[int]] = {
     'seed': [],

tools/replay/lib/ui_helpers.py

@@ -161,7 +161,7 @@ def init_plots(arr, name_to_arr_idx, plot_xlims, plot_ylims, plot_names, plot_co
       idxs.append(name_to_arr_idx[item])
       plot_select.append(i)
     axs[i].set_title(", ".join(f"{nm} ({cl})"
-                               for (nm, cl) in zip(pl_list, plot_colors[i])), fontsize=10)
+                               for (nm, cl) in zip(pl_list, plot_colors[i], strict=True)), fontsize=10)
     axs[i].tick_params(axis="x", colors="white")
     axs[i].tick_params(axis="y", colors="white")
     axs[i].title.set_color("white")
@@ -205,11 +205,11 @@ def plot_model(m, img, calibration, top_down):
     px, py_bottom = to_topdown_pt(x - x_std, y)
     top_down[1][int(round(px - 4)):int(round(px + 4)), py_top:py_bottom] = find_color(top_down[0], YELLOW)
 
-  for path, prob, _ in zip(m.laneLines, m.laneLineProbs, m.laneLineStds):
+  for path, prob, _ in zip(m.laneLines, m.laneLineProbs, m.laneLineStds, strict=True):
     color = (0, int(255 * prob), 0)
     draw_path(path, color, img, calibration, top_down, YELLOW)
 
-  for edge, std in zip(m.roadEdges, m.roadEdgeStds):
+  for edge, std in zip(m.roadEdges, m.roadEdgeStds, strict=True):
     prob = max(1 - std, 0)
     color = (int(255 * prob), 0, 0)
     draw_path(edge, color, img, calibration, top_down, RED)