There are three common methods to find duplicate elements in Python lists: 1. Use loops and dictionary statistics; 2. Use collections.Counter to count efficiently; 3. Use collections to detect duplicates. The first method uses the list and uses a dictionary to record the number of occurrences of each element, and finally filters out elements with more than one occurrence, which is suitable for beginners to understand; the second method uses the Counter class in the standard library to automatically count, with concise and efficient code, which is the first choice for most developers; the third method uses two sets to record the seen elements and repeat elements respectively, which is suitable for scenarios where streaming data or memory savings are processed. Just choose the appropriate method according to the specific needs.
Finding duplicates in a Python list is actually pretty straightforward once you know which tools and methods to use. The key idea is to compare elements and track how many times each one appears. There are several ways to do this, ranged from basic loops to more efficient built-in tools.
Here are the most common approaches people use:
Use a loop and a dictionary to count occurences
This is a beginner-friendly method that uses a dictionary to keep track of how many times each item shows up.
You can loop through the list, and for each item, increment its count in the dictionary. Then, you just filter out items that appear more than once.
my_list = [1, 2, 3, 2, 4, 5, 1]
duplicates = {}
for item in my_list:
if item in duplicates:
duplicates[item] = 1
else:
duplicates[item] = 1
# Get items that appeared more than once
result = [k for k, v in duplicates.items() if v > 1]This method gives you full visibility into what's happening under the hood and works well for small to medium-sized lists.
Use collections.Counter
If you're OK using Python's standard library, collections.Counter is a clean and efficient way to find duplicates.
It automatically counts how many times each item appears, and from there, it's easy to extract duplicates.
from collections import Counter my_list = [1, 2, 3, 2, 4, 5, 1] counts = Counter(my_list) duplicates = [item for item, count in counts.items() if count > 1]
This is usually the go-to method for many developers because it's readable and fast enough for most practical cases.
Use sets to detect duplicates while iterating
Another clever trick involves using two sets: one to track see items and another to store duplicates.
- As you loop through the list, add items to the "seen" set.
- If an item is already in the "seen" set, add it to the "duplicates" set.
my_list = [1, 2, 3, 2, 4, 5, 1]
see = set()
duplicates = set()
for item in my_list:
if item in see:
duplicates.add(item)
else:
seen.add(item)This method stops checking for duplicates as soon as it knows an item is repeated, so it can be more memory-efficient in some cases.
Depending on your needs — readability, performance, or simplicity — any of these methods should work fine. For most everyday use, going with collections.Counter is probably the smoothest choice. But if you're avoiding imports or dealing with streaming data, the set-based method might come in handy.
Basically that's it.
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