rglob vs glob: Which Is Faster in Python?

Intro — what this post promises

In Python, Path.rglob("*") and glob.glob("**/*", recursive=True) are effectively the same speed for listing files: 5.95 ms vs 6.19 ms on a 1,210-file tree with Python 3.13.5, because both return directories too and pay for an is_file check on every hit. If raw speed matters, os.walk listed the same files in 1.30 ms (about 4.6x faster than rglob and 4.8x faster than glob), so use rglob for Path ergonomics and walk for bulk listing

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Lab honesty (1 Oct 2026 IST): Python 3.13.5. Fixture at lab-evidence/76-glob-vs-rglob-vs-walk/fixture_tree/. Affiliates: 0. “Files” arms filter isfile / is_file(); “all” arms include directories.

Verdict up front (modest, 1,210 files): os.walk ~1.30 ms (~929k/s) vs rglob+is_file ~5.95 ms vs glob+isfile ~6.19 ms. Walk led glob by ~4.8× and rglob by ~4.6×. Prefer os.walk for raw listing speed; rglob for Path ergonomics.

Arms

Trees: modest (depth 2) and wider (depth 3).

Lab topology

modest: ~1210 files; wider: ~4170 files
metric: p50 wall; entries/s
fixture persisted under lab-evidence/76-.../fixture_tree/

Script: lab-evidence/76-glob-vs-rglob-vs-walk/results/run_lab.py.

Lead table — modest tree (p50)

Wider tree (4,170 files)

Same ranking at larger scale: walk ~4.7× glob files.

Reading it

• os.walk wins listing — fewer Path object allocations; classic C-backed scandir walk.
• rglob ≈ glob for files after is_file filters (~1.04× modest).
• Filtering is costly — “all entries” glob/rglob is much closer to walk; isfile checks dominate the files arms.
• Use Path when you need Path methods next; don’t pick rglob expecting a speedup over walk.

Fixture note

The tree is generated into evidence so you can re-list the same shape. It is not a kernel FS stress test — enough files to rank APIs, not millions of inodes.

Why isfile filters hurt

glob/rglob return directory entries too. Turning that into a file list means a metadata check per path. os.walk already separates dirnames from filenames, so the files arm mostly pays string joins. If you only need counts or names inside each directory, stay on walk and avoid a second pass of Path.is_file().

Pitfalls

1. Comparing glob-all to walk-files — different entry sets (dirs included).
2. Calling Path.is_file() on every rglob hit without needing stat — expensive.
3. Assuming recursive glob is “free” — pattern matching + filters add up.
4. Network FS / huge trees — re-measure; locality matters.

When to pick what

FAQ

What is the difference between glob and rglob?

Path.rglob(pattern) is Path.glob("**/" + pattern): it always searches recursively and returns Path objects. glob.glob needs "**" plus recursive=True and returns strings.

Is rglob faster than glob?

Not meaningfully. For files they were within about 1.04x on the 1,210-file tree (5.95 ms vs 6.19 ms) and similar on 4,170 files (22.52 ms vs 21.43 ms).

What is the fastest way to list all files recursively in Python?

os.walk in this lab: 1.30 ms (~929k files/s) on 1,210 files and 4.57 ms on 4,170 files, because it already separates filenames from dirnames.

Reproduce

python3 lab-evidence/76-glob-vs-rglob-vs-walk/results/run_lab.py

Evidence: /workspace/lab-evidence/76-glob-vs-rglob-vs-walk/results/ (+ fixture_tree/).

Closing

Walk to list; Path to ergonomics. On this box modest walk hit ~929k files/s, about ~4.8× glob+isfile and ~4.6× rglob+is_file. Reach for recursive glob when the pattern is the product; reach for walk when the product is “all files under here, fast.”