Maximizing LINE Number Filter Efficiency
Hey there, I've been working on optimizing a LINE number filter for a project I'm working on, and I could use some input. Have you ever tackled something similar? I'm dealing with a huge dataset with all sorts of phone numbers, and I need to filter out the ones that belong to South Korea.
I figured out that South Korean phone numbers usually start with a specific pattern, but the process is taking a bit longer than I'd like. Any tips on how to make it faster?
One idea I had was to create a regex pattern that matches the start of the South Korean phone numbers. But I'm wondering if there's a more efficient way to filter them out without having to iterate through every single number.
Regex to the Rescue?
I tried using a regex pattern like ^82\d{2,3} to match the South Korean numbers, but it's still a bit slow. Maybe there are some optimizations or alternatives I haven't thought of?
Or maybe I'm overthinking it and sticking to a simple regex pattern is the best way to go. What do you think?
Considering Alternatives
Another thought I had was to use a lookup table or a dictionary to compare the numbers against known South Korean prefixes. Would that be faster than regex?
But then again, managing a large dictionary might add its own set of challenges. Thoughts on that?
Mixed Bag of Ideas
Maybe there's a way to preprocess the data, grouping numbers by the first few digits and then applying the filters. That could potentially speed things up, but it might also require a bit more setup time.
I'd love to hear your thoughts on these ideas. Anyone else out there working on something similar? It always helps to bounce ideas around with someone else.
Let's Collaborate!
If you have any clever optimizations or suggestions, let me know. I'm always looking for ways to improve my processes and make things run smoother.
Thanks a bunch for any advice you can offer!