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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _generate_sequences_for_ngram(self, t1, t2, ngram, covered_spans):
 """Generates aligned sequences for the texts `t1` and `t2`, based around `ngram`. Does not generate sequences that occur within `covered_spans`. :param t1: text content of first witness :type t1: `str` :param t2: text content of second witness :type t2: `str` :param ngram: n-gram to base sequences on :type ngram: `str` :param covered_spans: lists of start and end indices for parts of the texts already covered by a sequence :type covered_spans: `list` of two `list`s of 2-`tuple` of `int` """

        self._logger.debug('Generating sequences for n-gram "{}"'.format(
            ngram))
        pattern = re.compile(re.escape(ngram))
        context_length = len(ngram)
        t1_spans = [match.span() for match in pattern.finditer(t1)]
        t2_spans = [match.span() for match in pattern.finditer(t2)]
        sequences = []
        self._logger.debug(t1)
        for t1_span in t1_spans:
            for t2_span in t2_spans:
                if self._is_inside(t1_span, t2_span, covered_spans):
                    self._logger.debug(
                        'Skipping match due to existing coverage')
                    continue
                sequence = self._generate_sequence(
                    t1, t1_span, t2, t2_span, context_length, covered_spans)
                if sequence:
                    sequences.append(sequence)
        return sequences