ezfs 1.0.1

Minimalistic virtual filesystem adapters for Python

EZFS

EZFS is an optimized, minimal dependency (down to 0), virtual filesystem adapter library for Python. The library provides abstraction layers for reading and writing to various backend storage solutions with a single frontend. Reading and writing is supported for text and binary files across local, remote, and memory "filesystems". Additional compression types and storage types can be supported by extending the primary File, Filesystem, and Compressor adapters.

Table Of Contents

• Compatibility
• Getting Started
  • Installation
• How Tos
  • Write a file with compress
  • Read a file with compress
  • Access a file (object) in an S3 bucket, and use compression
• Why EZFS?
  • What does EZFS provide?
  • What does EZFS not provide?
  • Dependency Simplicity Example
  • Optimized Remote Filesystem Example
• Contributing

Compatibility

• Supports Python 3.10+
• Supports multiple compression types
  • bz2, gzip, lzma (when built into Python)
  • blosc, brotli, lz4, snappy, and zstd (when installed separately)
• Support multiple storage types
  • sqlite3 (when built into Python)
  • S3 (when installed separately)
• Theoretically any compression type, or backend storage type, by extending Compressor, File, and Filesystem

Getting Started

Installation

Install EZFS via pip:

pip install ezfs

Or via git clone:

git clone <path to fork>
cd ezfs
pip install .

Or build and install from wheel:

# Build locally.
git clone <path to fork>
cd ezfs
make wheel

# Push dist/ezfs*.tar.gz to environment where it will be installed.
pip install dist/ezfs*.tar.gz

Or via copy and paste (only a single file is required):

# Copy:
cp ezfs.py <target project directory>

How Tos

EZFS filesystems and file objects are designed to work nearly identical to native open() file handles. Basic read and write operations can be directly swapped out after creating a filesystem adapter, and calling open() against the filesystem instead of Python built-ins, or 3rd party compression libraries. Here are a few examples of how to use the more advanced features, such as compression and remote storage.

Write a file with compression

import ezfs

filesystem = ezfs.LocalFilesystem('/tmp')
with filesystem.open('test-file.txt.gz', 'w+', compression='gzip') as out_file:
    out_file.write('test message')

# Or automatically compress all files on the "filesystem" on write:
filesystem = ezfs.LocalFilesystem('/tmp', compression='gzip')
with filesystem.open('test-file.txt.gz', 'w+') as out_file:
    out_file.write('test message')

Read a file with compression

import ezfs

filesystem = ezfs.LocalFilesystem('/tmp')
with filesystem.open('test-file.txt.gz', compression='gzip') as in_file:
    print(in_file.read())

# Or automatically decompress all files on the "filesystem" on read:
filesystem = ezfs.LocalFilesystem('/tmp', compression='gzip')
with filesystem.open('test-file.txt.gz') as in_file:
    print(in_file.read())

Access a file (object) in an S3 bucket, and use compression

import ezfs

# To use advanced compression types, they must be installed separately.
filesystem = ezfs.S3BotoFilesystem(
    'my-bucket-1234',
    access_key_id='ABC123',
    secret_access_key='abcdefg1234567',
    compression='zstd',
)
with filesystem.open('test-file.txt.zst', 'w+') as out_file:
    out_file.write('test message')
with filesystem.open('test-file.txt.zst') as in_file:
    print(in_file.read())

Why EZFS?

To simplify simple use cases.

EZFS is a very lightweight library (one file!), used to optimize simple use cases, or provide a starting point for more complex use cases. While there are other libraries that can help accomplish filesystem-like use cases depending on the backend, such as s3fs for S3, they may be more than needed or wanted. For example, perhaps you have predictable logic to store/read files, and don't need to browse the filesystem tree. Perhaps you want to leverage a custom service to act as storage interchangeably with local files, without installing extra dependencies from other solutions. EZFS adapters can help with that. If you need full metadata support like filesystem tree browsing, or file permissions, EZFS cannot help with that (natively), and recommends using a more feature rich solution, or extending the adapters to fit your needs.

What does EZFS provide?

EZFS provides a shared, optimized, interface to read and write files to various backend locations, with or without compression. The backend for the storage can often be changed with a single line, without changing the rest of the code.

What does EZFS not provide?

EZFS does not provide a complex feature set for advanced use cases, such as managing permissions or other metadata on filesystems. EZFS also not provide streaming interfaces for processing larger than memory files in "chunks".

Dependency Simplicity Example

Here is an example of using a library such as sf3s vs ezfs for basic read and write to S3, and its effect on required dependencies in a project. A basic boto3 install (only requirement for ezfs support) will add the following to the environment:

• boto3
• botocore
• jmespath
• python-dateutil
• s3transfer
• six
• urllib3

An s3fs install will add the following in addition to the core boto3 requirements:

• aiobotocore
• aiohttp
• aioitertools
• aiosignal
• async-timeout
• attrs
• idna
• frozenlist
• fsspec
• multidict
• s3fs
• wrapt
• yarl

Perhaps you already have all these requirements. Great! Then S3FS may be a better fit. Perhaps you don't have these, and want to reduce requirements that may add maintenance overhead to resolve security vulnerabilities. Great! EZFS may be a better fit. Still not sure? Continue reading for a performance example.

Optimized Remote Filesystem Example

Here is a basic performance example, using S3 + pandas to store DataFrames. By using a Filesystem adapter to store the results, it can optimize the S3 client used to reduce networking overhead. The optimization benefit is greater with small files, but even larger files benefit, and the simplicity to use stays the same.

• Small file: 100K
• Large file: 1M
• 100 iterations per test

Scenario	Write	Read
pandas s3fs small raw	25 sec	15.6 sec
pandas ezfs small raw	16.9 sec	8.39 sec
pandas s3fs large raw	47.3 sec	17.9 sec
pandas ezfs large raw	28.7 sec	11.2 sec
pandas s3fs small zstd	20.2 sec	12 sec
pandas ezfs small zstd	12.6 sec	6.76 sec
pandas s3fs large zstd	37.4 sec	18.1 sec
pandas ezfs large zstd	21.5 sec	11.1 sec

Contributing

EZFS is not currently accepting new features. Minor features may be added to improve the native use cases, but outside minor changes it will only receive bug fixes and dependency updates. This decision is to ensure EZFS will stay focused on its primary goal: stay simple and efficient, by focusing on simple use cases. Feel free to import, fork, copy, etc., to other projects to expand the scope of its ecosystem. Refer to the Contributing Guide for information on how to contribute to this project.