Python: What is a faster way to check if items in a large list are not in another large list?-CodePudding

I have two lists:

old_data has a length of 180,000.
updated_data has a length of 184,000.
Both lists contain IDs which are string values.
There is a lot of overlap in IDs stored within the lists but I need to know which ones are no longer stored in updated_data so that I can say those IDs are not longer active in an SQL server.

Therefore, I need to check for any items in old_data that are not in updated_data and save them to a separate list, let's call it inactive_data.

I have the following code currently which is highly time-consuming and inefficient:

# Initialize list for no-longer active IDs to be saved into.
inactive_data = []

# Iteratively check if all IDs in old data are still in updated data.
# If they are not, add them to the list.
for Id in old_data:
    
    if Id not in updated_data:
        
        inactive_data.append(Id)

To run this code, it took approx. 45 minutes. I would to know how I could drastically reduce the time. If you have any suggestions please let me know!

CodePudding user response：

Give it a go

old_data = set(map(tuple, inactive_data))
new_data= set(map(tuple, updated_data))

print([i for i in old_dataif i not in new_data])

CodePudding user response：

The usual and easy way is to turn one or both of the list into a set.

An alternate way is to sort both lists and compare them element by element. Once they're ordered, the comparison is quick because it's O(n).

CodePudding user response：

You can first convert updated_data into a set, and then use in; in operator on a set is very fast (O(1)).

import random

m, n = 180000, 184000
old_data = [random.randrange(m) for _ in range(m)]
updated_data = [random.randrange(n) for _ in range(n)]

updated_data = set(updated_data)
inactive_data = [x for x in old_data if x not in updated_data]

The above code takes less than 1 second on my machine.