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A fast directory scanner.

Project description


scandir_rs is a directory iteration module like os.walk(), but with more features and higher speed. Depending on the function call it yields a list of paths, tuple of lists grouped by their entry type or DirEntry objects that include file type and stat information along with the name. Using scandir_rs is about 2-17 times faster than os.walk() (depending on the platform, file system and file tree structure) by parallelizing the iteration in background.

If your are just interested in directory statistics you can use the submodule count.

scandir_rs contains following submodules:

  • count for determining statistics of a directory.
  • walk for getting names of directory entries.
  • scandir for getting detailed stats of directory entries.

For the API see:


For building this wheel from source you need Rust with channel nightly and the tool maturin.

Switch to channel nightly:

rustup default nightly

Install maturin:

cargo install maturin

Build wheel:

maturin build --release

maturin will build the wheels for all Python versions installed on your system.


Get statistics of a directory:

import scandir_rs as scandir

print(scandir.count.count("~/workspace", extended=True))

The same, but asynchronously in background using a class instance:

import scandir_rs as scandir

scanner = scandir.count.Count("~/workspace", extended=True))
scanner.start())  # Start background thread pool
value = scanner.statistics  # Can be read at any time
scanner.stop()  # If you want to cancel the scanner

and with a context manager:

import scandir_rs as scandir

C = scandir.count.Count("~/workspace", extended=True))
with C:
    while C.busy():
        statistics = C.statistics
        # Do something

os.walk() example:

import scandir_rs as scandir

for root, dirs, files in scandir.walk.Walk("~/workspace"):
    # Do something

os.scandir() example:

import scandir_rs as scandir

for entry in scandir.scandir.Scandir("~/workspace", metadata_ext=True):
    # Do something


See examples/

In the below table the line scandir_rs.walk.Walk returns comparable results to os.walk.

Linux with Ryzen 5 2400G and SSD

Directory ~/workspace with

  • 22845 directories
  • 321354 files
  • 130 symlinks
  • 22849 hardlinks
  • 4 devices
  • 1 pipes
  • 4.6GB size and 5.4GB usage on disk
Time [s] Method
0.547 os.walk (Python 3.7)
0.132 scandir_rs.count.count
0.142 scandir_rs.count.Count
0.237 scandir_rs.walk.Walk
0.224 scandir_rs.walk.toc
0.242 scandir_rs.walk.collect
0.262 scandir_rs.scandir.entries
0.344 scandir_rs.scandir.entries(metadata=True)
0.336 scandir_rs.scandir.entries(metadata_ext=True)
0.280 scandir_rs.scandir.Scandir.collect
0.262 scandir_rs.scandir.Scandir.iter
0.330 scandir_rs.scandir.Scandir.iter(metadata_ext=True)

Up to 2 times faster on Linux.

Windows 10 with Laptop Core i7-4810MQ @ 2.8GHz Laptop, MTF SSD

Directory C:\Windows with

  • 84248 directories
  • 293108 files
  • 44.4GB size and 45.2GB usage on disk
Time [s] Method
26.881 os.walk (Python 3.7)
4.094 scandir_rs.count.count
3.654 scandir_rs.count.Count
3.978 scandir_rs.walk.Walk
3.848 scandir_rs.walk.toc
3.777 scandir_rs.walk.collect
3.987 scandir_rs.scandir.entries
3.905 scandir_rs.scandir.entries(metadata=True)
4.062 scandir_rs.scandir.entries(metadata_ext=True)
3.934 scandir_rs.scandir.Scandir.collect
3.981 scandir_rs.scandir.Scandir.iter
3.821 scandir_rs.scandir.Scandir.iter(metadata_ext=True)

Up to 6.7 times faster on Windows 10.

Directory C:\testdir with

  • 185563 directories
  • 1641277 files
  • 2696 symlinks
  • 97GB size and 100.5GB usage on disk
Time [s] Method
151.143 os.walk (Python 3.7)
7.549 scandir_rs.count.count
7.531 scandir_rs.count.Count
8.710 scandir_rs.walk.Walk
8.625 scandir_rs.walk.toc
8.599 scandir_rs.walk.collect
9.014 scandir_rs.scandir.entries
9.208 scandir_rs.scandir.entries(metadata=True)
8.925 scandir_rs.scandir.entries(metadata_ext=True)
9.243 scandir_rs.scandir.Scandir.collect
8.462 scandir_rs.scandir.Scandir.iter
8.380 scandir_rs.scandir.Scandir.iter(metadata_ext=True)

Up to 17.4 times faster on Windows 10.

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