Python遍历嵌套列表子元素配对提取序列时索引错误，如何优化实现？

• 首要原因是populated_indices的长度和pca_df的行数不匹配：当循环中index的值超过populated_indices的最大下标时，取populated_indices[index]就会抛出IndexError
• 次要原因是双指针的遍历写法冗余，容易出现边界逻辑错误

基础实现（无需引入额外库） #

直接利用列表步长切片配对，逻辑清晰不易出错：

lst_separated = [['1605',1607],['230320','230400','25020','26232'],['230320','230400','25020','26232','302320','312320'],...]
# 提前做长度校验，从根源避免越界
assert len(populated_indices) == len(pca_df), "populated_indices长度和pca_df行数不匹配"
populated_lists = [lst_separated[i] for i in populated_indices]
outcome = []

for seqName, sublist in zip(pca_df['seqName'], populated_lists):
    # 两两配对：取奇数位元素和偶数位元素一一对应，长度为奇数时自动丢弃最后一个不匹配的元素
    for pos1, pos2 in zip(sublist[::2], sublist[1::2]):
        start = int(pos1) - 1
        end = int(pos2) - 1
        var = str(record_dict_2[seqName].seq)[start:end]
        outcome.append(var)

itertools实现（适合大列表场景，内存效率更高） #

用迭代器实现配对，避免生成临时切片，超大子列表场景下性能优势更明显：

from itertools import islice

lst_separated = [['1605',1607],['230320','230400','25020','26232'],['230320','230400','25020','26232','302320','312320'],...]
assert len(populated_indices) == len(pca_df), "populated_indices长度和pca_df行数不匹配"
populated_lists = [lst_separated[i] for i in populated_indices]
outcome = []

for seqName, sublist in zip(pca_df['seqName'], populated_lists):
    iter_s = iter(sublist)
    # 迭代器每次调用都会自动移动指针，两次取同一个迭代器的值自然实现两两配对
    for pos1, pos2 in zip(iter_s, iter_s):
        start = int(pos1) - 1
        end = int(pos2) - 1
        var = str(record_dict_2[seqName].seq)[start:end]
        outcome.append(var)

内容的提问来源于stack exchange，提问作者user17153595