I'm working on a Python program running in WSL on Ubuntu. Because my program generates a large amount of redundant coordinate data, an in-memory list eventually becomes too large. I wondered whether I could reduce the memory usage by representing the data as paths made up of millions of nested empty folders, with each folder encoding information about the route to a datum. Could this approach cause system instability or other serious problems, and is there a better way to store the data?
4 Answers
Deep nesting also runs into pathname-length limits. Windows and Unix-like systems impose limits on how long a complete path can be, so you cannot keep nesting directories indefinitely. Even before reaching that limit, filesystem operations will become increasingly impractical.
The memory problem suggests changing the data structure or processing strategy rather than moving the same information into folders. Consider streaming the coordinates, deduplicating them as you generate them, using a set or a compact representation, or storing them incrementally in SQLite. A nested dictionary or another on-disk key-value structure could also work if the data naturally forms a hierarchy.
The biggest issue is that a filesystem is probably the wrong tool for this job. Empty folders still consume metadata and inode space, and millions of entries can make indexing, backups, searches, and cleanup painfully slow. If the disk fills up, other applications can become unstable too. A database such as SQLite would be a much more appropriate way to store coordinates and eliminate duplicates.
If you need a filesystem-based layout for content identified by hashes, use a shallow tree instead of one directory per piece of information. For example, use a few leading characters of a hash as separate directory levels, then store the item in the final directory. That keeps any one directory manageable, but a database is still likely better for coordinate data.

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