pyofiles 0.4.0

Fast, Rust-powered file operations for Python

pyofiles

Fast, Rust-powered file operations for Python. Drop-in replacements for os.walk, os.listdir, and glob.glob -- built on parallel directory walkers for maximum speed.

Install

uv add pyofiles

or with pip:

pip install pyofiles

CLI

pyofiles includes a command-line interface. Run directly with uvx:

uvx pyofiles find . --ext .py --modified-after 7d

Or install globally with uv tool:

uv tool install pyofiles

Version

pyofiles --version
pyofiles -v

You can also check the version from Python:

import pyofiles
print(pyofiles.__version__)

Examples

# Walk a directory, showing only Python files
pyofiles walk ./src --ext .py --skip-hidden

# Long format: type, size, modified time, path
pyofiles walk ./src --ext .py -l

# Walk with name and size filters
pyofiles walk ./src --names main utils --min-size 0.001

# Find files by name substring
pyofiles find ./data --names report invoice --ext .pdf

# Find files modified in the last 7 days
pyofiles find ./project --ext .py --modified-after 7d

# Find files created before a specific date
pyofiles find ./logs --ext .log --created-before 2024-06-01

# Find large files modified recently
pyofiles find ./data --ext .csv --min-size 100 --modified-after 24h

# Find by size alone
pyofiles find . --min-size 500

# Glob pattern matching (with time/size filters)
pyofiles glob ./project "**/*.rs"
pyofiles glob ./project "**/*.py" --modified-after 7d --max-depth 3

# List directory contents (with filters)
pyofiles ls ./some/dir -l
pyofiles ls ./src --ext .py --skip-hidden

# Index files by stem (with time filters)
pyofiles index ./src --ext .py .pyi .pyc
pyofiles index ./src --ext .py --created-after 2024-01-01

# Disk usage analysis (with extension/time/name filters)
pyofiles du ./project --depth 2 --top 10
pyofiles du ./project --ext .py --modified-after 30d
pyofiles du ./project --names test --ext .py

# JSON output (works with all commands, pipe to jq)
pyofiles find ./src --ext .py --json
pyofiles du . --json | jq '.entries[:5]'

Time formats

Time arguments (--modified-after, --modified-before, --created-after, --created-before) accept:

Format	Example	Meaning
Relative duration	7d, 24h, 30m, 1w	ago from now
ISO date	2024-03-15	midnight on that date
ISO datetime	2024-03-15T10:30:00	specific moment
Unix timestamp	1709251200	raw epoch seconds

Filter availability

All filters are available across commands where they make sense:

Filter	walk	find	ls	glob	index	du
--ext	yes	yes	yes	—	yes (required)	yes
--names	yes	yes	yes	—	yes	yes
--min/max-size	yes	yes	yes	yes	yes	yes
--skip-hidden	yes	yes	yes	yes	yes	yes
--max-depth	yes	yes	—	yes	yes	—
time filters	yes	yes	yes	yes	yes	yes

Python API

walk(directory, extensions=None, skip_hidden=False, max_depth=None, names=None, min_size_mb=None, max_size_mb=None, modified_after=None, modified_before=None, created_after=None, created_before=None)

Parallel recursive directory walk. Returns list[FileEntry].

import pyofiles

# Walk everything
entries = pyofiles.walk("/path/to/dir")

# Only Python files
entries = pyofiles.walk("/path", extensions=[".py"])

# Files modified in the last 24 hours
import time
recent = pyofiles.walk("/path", modified_after=time.time() - 86400)

# Walk with name and size filters
entries = pyofiles.walk("/path", names=["test"], min_size_mb=0.01)

for e in entries:
    if e.is_file:
        print(f"{e.name} ({e.size} bytes)")

find(directory, names=None, extensions=None, min_size_mb=None, max_size_mb=None, skip_hidden=False, max_depth=None, modified_after=None, modified_before=None, created_after=None, created_before=None)

Search for files by name substrings, extensions, size, and time. Accepts multiple substrings -- a file matches if its name contains ANY of them (case-insensitive).

# Find files containing "report" or "invoice" in the name
results = pyofiles.find("/data", names=["report", "invoice"])

# Find large videos
results = pyofiles.find("/media", extensions=[".mp4", ".avi"], min_size_mb=100)

# Combine: name + extension + size
results = pyofiles.find("/docs", names=["2024"], extensions=[".pdf"], max_size_mb=50)

# Find recently modified Python files
results = pyofiles.find("/src", extensions=[".py"], modified_after=time.time() - 7*86400)

# Find files created in a date range
results = pyofiles.find("/logs", names=["error"],
                        created_after=1709251200, created_before=1711929600)

# Find by size alone
results = pyofiles.find("/data", min_size_mb=500)

list_dir(directory, extensions=None, names=None, min_size_mb=None, max_size_mb=None, skip_hidden=False, modified_after=None, modified_before=None, created_after=None, created_before=None)

Non-recursive single-directory listing. Returns list[FileEntry].

entries = pyofiles.list_dir("/path")

# List only Python files, skip hidden
entries = pyofiles.list_dir("/src", extensions=[".py"], skip_hidden=True)

# List recently modified files
entries = pyofiles.list_dir("/data", modified_after=time.time() - 86400)

index(directory, extensions, skip_hidden=False, max_depth=None, names=None, min_size_mb=None, max_size_mb=None, modified_after=None, modified_before=None, created_after=None, created_before=None)

Build a file index grouped by filename stem. Useful for finding related files with different extensions.

idx = pyofiles.index("/src", extensions=[".py", ".pyi", ".pyc"])
# {"main": {".py": "/src/main.py", ".pyc": "/src/__pycache__/main.pyc"}}

# Index only recently modified files
idx = pyofiles.index("/src", extensions=[".py"], modified_after=time.time() - 7*86400)

# Index with depth limit
idx = pyofiles.index("/project", extensions=[".py"], max_depth=3)

glob(directory, pattern, skip_hidden=False, max_depth=None, min_size_mb=None, max_size_mb=None, modified_after=None, modified_before=None, created_after=None, created_before=None)

Parallel glob pattern matching. Returns list[str] of full paths.

paths = pyofiles.glob("/project", "**/*.py")
paths = pyofiles.glob("/project", "src/**/*.{rs,toml}")

# Glob with time filter
paths = pyofiles.glob("/project", "**/*.py", modified_after=time.time() - 7*86400)

# Glob with size filter
paths = pyofiles.glob("/data", "**/*.csv", min_size_mb=10)

disk_usage(directory, depth=1, top=20, skip_hidden=False, extensions=None, names=None, min_size_mb=None, max_size_mb=None, modified_after=None, modified_before=None, created_after=None, created_before=None)

Analyze disk space usage by directory. Returns a DiskUsage object.

usage = pyofiles.disk_usage("/home", depth=2, top=10)
print(f"Total: {usage.total_size_gb:.2f} GB across {usage.total_files} files")
for entry in usage.entries:
    print(f"  {entry.path}: {entry.size_mb:.1f} MB ({entry.file_count} files)")

# Disk usage for Python files only
usage = pyofiles.disk_usage("/project", extensions=[".py"])

# Disk usage of recently modified files
usage = pyofiles.disk_usage("/project", modified_after=time.time() - 30*86400)

# Disk usage of test files
usage = pyofiles.disk_usage("/project", names=["test"], extensions=[".py"])

Types

FileEntry

Returned by walk, find, list_dir.

Attribute	Type
path	str
name	str
is_file	bool
is_dir	bool
size	int
extension	str
modified	float or None
created	float or None

Timestamps are unix epoch seconds. Use datetime.fromtimestamp(entry.modified) to convert. created may be None on Linux systems that don't support creation time.

SizeEntry

Returned inside DiskUsage.entries.

Attribute	Type
path	str
size	int
file_count	int
size_mb	float
size_gb	float

DiskUsage

Returned by disk_usage.

Attribute	Type
entries	list[SizeEntry]
total_size	int
total_files	int
total_size_mb	float
total_size_gb	float

Performance

Built on jwalk (parallel directory walker) and PyO3. Typically 5-50x faster than equivalent Python code, especially on large directories and network drives.

License

MIT