Fix Bug: When using Nuitka to package a project, an error occurred wh…

…en reading the file: "KeyError: 'self'" mne-tools#12923

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 repos:
   # Ruff mne
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.7.0
+    rev: v0.7.1
     hooks:
       - id: ruff
         name: ruff lint mne

mne/io/ant/ant.py

@@ -157,6 +157,9 @@ def __init__(
             "first_samples": np.array(first_samps),
             "last_samples": np.array(last_samps),
         }
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload=preload,

mne/io/array/array.py

@@ -83,6 +83,9 @@ def __init__(self, data, info, first_samp=0, copy="auto", verbose=None):
             f"Creating RawArray with {dtype.__name__} data, "
             f"n_channels={data.shape[0]}, n_times={data.shape[1]}"
         )
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info, data, first_samps=(int(first_samp),), dtype=dtype, verbose=verbose
         )

mne/io/artemis123/artemis123.py

@@ -358,6 +358,8 @@ def __init__(
 
         last_samps = [header_info.get("num_samples", 1) - 1]
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/boxy/boxy.py

@@ -168,6 +168,9 @@ def __init__(self, fname, preload=False, verbose=None):
         assert len(raw_extras["offsets"]) == delta + 1
         if filetype == "non-parsed":
             delta //= raw_extras["source_num"]
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/brainvision/brainvision.py

@@ -126,6 +126,9 @@ def __init__(
 
         orig_format = "single" if isinstance(fmt, dict) else fmt
         raw_extras = dict(offsets=offsets, fmt=fmt, order=order, n_samples=n_samples)
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             last_samps=[n_samples - 1],

mne/io/bti/bti.py

@@ -1007,6 +1007,7 @@ def __init__(
         filename = bti_info["pdf"]
         if isinstance(filename, BytesIO):
             filename = None
+        __import__("inspect").currentframe().f_locals.update(locals())
         super().__init__(
             info,
             preload,

mne/io/cnt/cnt.py

@@ -536,6 +536,7 @@ def __init__(
                 "please use mne.io.read_raw_ant instead."
             )
         last_samps = [cnt_info["n_samples"] - 1]
+        __import__("inspect").currentframe().f_locals.update(locals())
         super().__init__(
             info,
             preload,

mne/io/ctf/ctf.py

@@ -162,6 +162,9 @@ def __init__(
                 f"file(s): {missing_names}, and the following file(s) had no "
                 f"valid samples: {no_samps}"
             )
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/curry/curry.py

@@ -593,6 +593,8 @@ def __init__(self, fname, preload=False, verbose=None):
         last_samps = [n_samples - 1]
         raw_extras = dict(is_ascii=is_ascii)
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/edf/edf.py

@@ -185,6 +185,9 @@ def __init__(
 
         # Raw attributes
         last_samps = [edf_info["nsamples"] - 1]
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/eeglab/eeglab.py

@@ -463,6 +463,8 @@ def __init__(
             data_fname = _check_eeglab_fname(input_fname, eeg.data)
             logger.info(f"Reading {data_fname}")
 
+            __import__("inspect").currentframe().f_locals.update(locals())
+
             super().__init__(
                 info,
                 preload,
@@ -487,6 +489,7 @@ def __init__(
             data = np.empty((n_chan, n_times), dtype=float)
             data[:n_chan] = eeg.data
             data *= CAL
+            __import__("inspect").currentframe().f_locals.update(locals())
             super().__init__(
                 info,
                 data,

mne/io/egi/egi.py

@@ -288,6 +288,9 @@ def __init__(
         orig_format = (
             egi_info["orig_format"] if egi_info["orig_format"] != "float" else "single"
         )
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/egi/egimff.py

@@ -545,6 +545,8 @@ def __init__(
                     % (pns_samples, eeg_samples)
                 )
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload=preload,

mne/io/eximia/eximia.py

@@ -90,6 +90,9 @@ def __init__(self, fname, preload=False, verbose=None):
             )
         for ch, cal in zip(info["chs"], cals):
             ch["cal"] = cal
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload=preload,

mne/io/eyelink/eyelink.py

@@ -105,6 +105,9 @@ def __init__(
             fname, find_overlaps, overlap_threshold, apply_offsets
         )
         # ======================== Create Raw Object =========================
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload=eye_ch_data,

mne/io/fiff/raw.py

@@ -130,6 +130,9 @@ def __init__(
         fname = _path_from_fname(fname)
 
         _check_raw_compatibility(raws)
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             copy.deepcopy(raws[0].info),
             preload=False,

mne/io/fil/fil.py

@@ -120,6 +120,8 @@ def __init__(self, binfile, precision="single", preload=False):
             meg = json.load(fid)
         info = _compose_meas_info(meg, chans)
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/hitachi/hitachi.py

@@ -101,6 +101,9 @@ def __init__(self, fname, preload=False, *, verbose=None):
         raw_extras = [dict(probes=probes)]
         # One representative filename is good enough here
         # (additional filenames indicate temporal concat, not ch concat)
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/kit/kit.py

@@ -155,6 +155,9 @@ def __init__(
         last_samps = [kit_info["n_samples"] - 1]
         self._raw_extras = [kit_info]
         _set_stimchannels(self, info, stim, stim_code)
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/nedf/nedf.py

@@ -151,6 +151,9 @@ def __init__(self, filename, preload=False, verbose=None):
         with info._unlock():
             info["meas_date"] = header["meas_date"]
         raw_extra = dict(dt=dt, dt_last=dt_last, n_full=n_full)
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload=preload,

mne/io/neuralynx/neuralynx.py

@@ -287,6 +287,8 @@ def __init__(
             description=["BAD_ACQ_SKIP"] * len(gap_start_ids),
         )
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info=info,
             last_samps=[sizes_sorted.sum() - 1],

mne/io/nicolet/nicolet.py

@@ -186,6 +186,9 @@ def __init__(
         input_fname = path.abspath(input_fname)
         info, header_info = _get_nicolet_info(input_fname, ch_type, eog, ecg, emg, misc)
         last_samps = [header_info["num_samples"] - 1]
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/nihon/nihon.py

@@ -414,6 +414,8 @@ def __init__(self, fname, preload=False, verbose=None):
             info["chs"][i_ch]["range"] = t_range
             info["chs"][i_ch]["cal"] = 1 / t_range
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload=preload,

mne/io/nirx/nirx.py

@@ -477,6 +477,8 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
                 annot_mask |= mask
                 nan_mask[key] = None  # shouldn't need again
 
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/nsx/nsx.py

@@ -194,6 +194,9 @@ def __init__(
         ) = _get_hdr_info(input_fname, stim_channel=stim_channel, eog=eog, misc=misc)
         raw_extras["orig_format"] = orig_format
         first_samps = (raw_extras["timestamp"][0],)
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             first_samps=first_samps,

mne/io/persyst/persyst.py

@@ -226,6 +226,9 @@ def __init__(self, fname, preload=False, verbose=None):
 
         raw_extras = {"dtype": dtype, "n_chs": n_chs, "n_samples": n_samples}
         # create Raw object
+
+        __import__("inspect").currentframe().f_locals.update(locals())
+
         super().__init__(
             info,
             preload,

mne/io/snirf/_snirf.py

@@ -463,6 +463,8 @@ def natural_keys(text):
                     with info._unlock():
                         info["subject_info"]["birthday"] = birthday
 
+            __import__("inspect").currentframe().f_locals.update(locals())
+
             super().__init__(
                 info,
                 preload,