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ts_102_221: support EF.ARR record decoding for DF, not just EF

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Sadly, the EF.ARR interpretation, specifically that of the AM_DO
depends on whether the rule is for a DF or EF.  As we don't know this,
allow the user to specify what kind of decode they would like, at least
in the file-specific read_arr_record + read_arr_records command.

Change-Id: I05e629e8b7dc705730d7039d2d0170ee24f8f844
This commit is contained in:
Harald Welte
2026-08-15 11:29:24 +02:00
parent bb362482e8
commit f4eb2f9356
1 changed files with 30 additions and 8 deletions
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pySim/ts_102_221.py
+30 -8
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@@ -17,6 +17,7 @@ You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>. along with this program. If not, see <http://www.gnu.org/licenses/>.
""" """
from bidict import bidict from bidict import bidict
import copy
from construct import Select, Const, Bit, Struct, Int16ub, FlagsEnum, GreedyString, ValidationError from construct import Select, Const, Bit, Struct, Int16ub, FlagsEnum, GreedyString, ValidationError
from construct import Optional as COptional, Computed from construct import Optional as COptional, Computed
@@ -732,36 +733,57 @@ class EF_ARR(LinFixedEF):
raise ValueError raise ValueError
return by_mode return by_mode
@staticmethod
def __get_do_sequence(decode_for_df : bool = False):
if decode_for_df:
return DataObjectSequence('arr', sequence=[AM_DO_DF, SC_DO])
else:
return DataObjectSequence('arr', sequence=[AM_DO_EF, SC_DO])
def _decode_record_bin(self, raw_bin_data, **kwargs): def _decode_record_bin(self, raw_bin_data, **kwargs):
# we can only guess if we should decode for EF or DF here :( # we can only guess if we should decode for EF or DF here, but our caller may
arr_seq = DataObjectSequence('arr', sequence=[AM_DO_EF, SC_DO]) # be able to pass us a hint:
arr_seq = self.__get_do_sequence(kwargs.get('decode_for_df', False))
dec = arr_seq.decode_multi(raw_bin_data) dec = arr_seq.decode_multi(raw_bin_data)
# we cannot pass the result through flatten() here, as we don't have a related # we cannot pass the result through flatten() here, as we don't have a related
# 'un-flattening' decoder, and hence would be unable to encode :( # 'un-flattening' decoder, and hence would be unable to encode :(
return dec[0] return dec[0]
def _encode_record_bin(self, in_json, **kwargs): def _encode_record_bin(self, in_json, **kwargs):
# we can only guess if we should decode for EF or DF here :( # we can only guess if we should decode for EF or DF here, but our caller may
arr_seq = DataObjectSequence('arr', sequence=[AM_DO_EF, SC_DO]) # be able to pass us a hint:
arr_seq = self.__get_do_sequence(kwargs.get('encode_for_df', False))
return arr_seq.encode_multi(in_json) return arr_seq.encode_multi(in_json)
@with_default_category('File-Specific Commands') @with_default_category('File-Specific Commands')
class AddlShellCommands(CommandSet): class AddlShellCommands(CommandSet):
@cmd2.with_argparser(LinFixedEF.ShellCommands.read_rec_dec_parser) read_arr_argparser = copy.deepcopy(LinFixedEF.ShellCommands.read_rec_dec_parser)
read_arr_argparser.add_argument('--decode-for-df', action='store_true',
help='Decode EF.ARR record as if used by a DF (default: EF)')
@cmd2.with_argparser(read_arr_argparser)
def do_read_arr_record(self, opts): def do_read_arr_record(self, opts):
"""Read one EF.ARR record in flattened, human-friendly form.""" """Read one EF.ARR record in flattened, human-friendly form."""
(data, _sw) = self._cmd.lchan.read_record_dec(opts.RECORD_NR) (hexdata, _sw) = self._cmd.lchan.read_record(opts.RECORD_NR)
data = self._cmd.lchan.selected_file._decode_record_bin(h2b(hexdata),
decode_for_df = opts.decode_for_df)
data = self._cmd.lchan.selected_file.flatten(data) data = self._cmd.lchan.selected_file.flatten(data)
self._cmd.poutput_json(data, opts.oneline) self._cmd.poutput_json(data, opts.oneline)
@cmd2.with_argparser(LinFixedEF.ShellCommands.read_recs_dec_parser) read_arrs_argparser = copy.deepcopy(LinFixedEF.ShellCommands.read_recs_dec_parser)
read_arrs_argparser.add_argument('--decode-for-df', action='store_true',
help='Decode EF.ARR records as if used by a DF (default: EF)')
@cmd2.with_argparser(read_arrs_argparser)
def do_read_arr_records(self, opts): def do_read_arr_records(self, opts):
"""Read + decode all EF.ARR records in flattened, human-friendly form.""" """Read + decode all EF.ARR records in flattened, human-friendly form."""
num_of_rec = self._cmd.lchan.selected_file_num_of_rec() num_of_rec = self._cmd.lchan.selected_file_num_of_rec()
# collect all results in list so they are rendered as JSON list when printing # collect all results in list so they are rendered as JSON list when printing
data_list = [] data_list = []
for recnr in range(1, 1 + num_of_rec): for recnr in range(1, 1 + num_of_rec):
(data, _sw) = self._cmd.lchan.read_record_dec(recnr) (hexdata, _sw) = self._cmd.lchan.read_record(recnr)
data = self._cmd.lchan.selected_file._decode_record_bin(h2b(hexdata),
decode_for_df = opts.decode_for_df)
data = self._cmd.lchan.selected_file.flatten(data) data = self._cmd.lchan.selected_file.flatten(data)
data_list.append(data) data_list.append(data)
self._cmd.poutput_json(data_list, opts.oneline) self._cmd.poutput_json(data_list, opts.oneline)