Best Desktop Tool or Script to Compare Large Lists?

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Asked By TechieExplorer42 On

I'm on the hunt for a desktop tool or a script that can help me compare really large text files, typically containing between 50,000 and 100,000 lines each. The functionality I'm looking for includes the ability to identify items that are exclusive to each list (i.e., only in A or only in B), find duplicates, and compile a deduplicated master list that contains unique items from both lists. Web tools usually cap the input at 5,000–7,000 lines, so I'm hoping for something more robust. Ideally, I'm looking for a Python-based desktop GUI or a script that won't crash with these large datasets. If I were coding this myself, I'd also like some advice on memory-efficient strategies for handling such a capacity. I'm aware that using set() is quicker than lists, but would specific libraries like Polars or Pandas be helpful for creating a simple GUI utility?

5 Answers

Answered By DataGuru On

Looking at what you're trying to do, it seems like setting up a database might be the best route for you. Even though 100k lines isn't a huge amount of data, the queries you're interested in require a structured approach. Most database tools allow you to create tables from CSV files and use SQL queries to manipulate and explore your data. This will save you a lot of hassle!

Answered By CodeMaster007 On

You might want to consider using a hashmap to check for duplicates, which can keep the order of insertion too. It’s not super hard to program, and honestly, 70k lines isn't too much; you could just load both files into memory and generate the comparison results. If you're familiar with Python, that can be a neat approach!

Answered By SortWizard On

If your data is already sorted, you can use sort and the `comm` command on a Linux machine or WSL to get the job done easily. It's pretty straightforward if you're comfortable with command line tools.

Answered By PythonNinja On

I’d actually suggest throwing those lists into two database tables using SQLite with Python's sqlite3 library. This way, you can leverage SQL queries to find what’s where, which would be super efficient, especially with larger datasets!

Answered By MemoryHacker On

To save on memory, consider creating hashes for each line and storing those along with the actual line in a lookup. If duplicates are a concern, you can have your lookup return the hashes and corresponding lines. This should simplify the comparison process.

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