Safer vs Atomicwrites in Python: Which Should You Use?

Apr 5, 2026

Python programming

I was reviewing some legacy Python code when I stumbled across this:

import json
from atomicwrites import atomic_write

def save_config(config_data):
    with atomic_write('config.json', overwrite=True) as f:
        json.dump(config_data, f)

Wait, atomicwrites? I’d heard that library was deprecated. Time to investigate what’s actually happening here and what I should use instead.

The Problem: Why Atomic File Writes Matter

Before diving into the comparison, let me show you what happens with a regular file write:

# DANGEROUS: What could go wrong?
import json

config = {"api_key": "secret123", "timeout": 30, "retries": 5}

with open('config.json', 'w') as f:
    json.dump(config, f)
    # If the program crashes right here...
    # Your config file is CORRUPTED

If your process gets killed, the power goes out, or disk fills up mid-write, you’re left with a corrupted file. No more API key. No more configuration. Good luck debugging that in production.

I’ve been burned by this before. A monitoring script I wrote crashed during a write and wiped its own state file. Not fun.

How Atomic Writes Solve This

The solution is simple: write to a temporary file first, then atomically replace the original.

┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
│   Step 1        │     │   Step 2        │     │   Step 3        │
│                 │     │                 │     │                 │
│ Write to temp   │ ──► │ Write complete  │ ──► │ Atomic rename   │
│ config.json.tmp │     │ (or crash)      │     │ tmp → config.js │
└─────────────────┘     └─────────────────┘     └─────────────────┘
                              │
                              ▼
                        If crash here:
                        Original file intact!

If anything goes wrong during the write, the original file stays untouched.

Safer vs Atomicwrites: The Comparison

Let me break down the key differences:

Feature              │ safer           │ atomicwrites
─────────────────────┼─────────────────┼────────────────────
Maintenance          │ Active          │ DEPRECATED (2020)
Stream support       │ Yes             │ No
API simplicity       │ simpler         │ more verbose
PyPI downloads/month │ ~500K           │ ~2M (legacy code)
Python versions      │ 3.7+            │ 3.5+
OS support           │ All major       │ All major

The Dealbreaker: Maintenance Status

I checked the atomicwrites repository:

atomicwrites GitHub:
- Last commit: 4+ years ago
- PyPI status: "This library is deprecated"
- Author's recommendation: Use alternatives

That’s a red flag for any production code. No security updates. No bug fixes. No Python version compatibility updates.

Using Safer: A Practical Guide

Here’s how I rewrote that config writer:

import json
import safer

def save_config(config_data):
    """Save config with atomic write protection."""
    with safer.open('config.json', 'w') as f:
        json.dump(config_data, f)
        # Original config.json unchanged until this completes

The API is actually simpler than atomicwrites. No overwrite=True needed.

Safer Works with Streams Too

This is where safer really shines. atomicwrites only works with file paths, but safer works with any stream-like object:

import safer
from io import StringIO

# Works with any file-like object
stream = StringIO()

with safer.printer(stream) as s:
    s.write("Line 1\n")
    s.write("Line 2\n")
    # If exception here, stream stays empty

# Stream only gets content if no exception occurred
print(stream.getvalue())  # "Line 1\nLine 2\n"

This flexibility is huge when you’re writing tests or working with in-memory buffers.

Migration Path: From Atomicwrites to Safer

If you have existing code using atomicwrites, here’s the migration:

# OLD (deprecated):
from atomicwrites import atomic_write

with atomic_write('data.json', overwrite=True) as f:
    json.dump(data, f)

# NEW (recommended):
import safer

with safer.open('data.json', 'w') as f:
    json.dump(data, f)

The changes are minimal. Just a different import and slightly simpler API.

Batch Migration Script

If you have many files to migrate:

import re
from pathlib import Path

def migrate_file(filepath):
    """Convert atomicwrites usage to safer in a Python file."""
    content = Path(filepath).read_text()

    # Replace import
    content = re.sub(
        r'from atomicwrites import atomic_write',
        'import safer',
        content
    )

    # Replace usage
    content = re.sub(
        r'atomic_write\(([^,]+),\s*overwrite=True\)',
        r'safer.open(\1, "w")',
        content
    )

    Path(filepath).write_text(content)

Common Mistakes to Avoid

Mistake 1: Using atomicwrites in New Projects

Don’t. Just don’t. Check your requirements.txt or pyproject.toml:

# requirements.txt
atomicwrites==1.4.1  # REMOVE THIS

Mistake 2: Not Understanding the Difference

safer        = Prevents partial writes (write-then-replace)
atomicwrites = Atomic file replacement (OS-level)

Both achieve the same goal, but safer is maintained.

Mistake 3: Ignoring the Deprecation Warning

If you’re seeing this in your logs:

DeprecationWarning: atomicwrites is deprecated, use safer instead

Don’t ignore it. Schedule time to migrate.

When Safer Really Shines

I found safer particularly useful for:

Configuration files: Critical data that must never corrupt
State files: Application state that gets updated frequently
Log rotation: When you need to atomically replace log files
Cache invalidation: Atomic cache file updates

import safer
import json
from datetime import datetime

def update_app_state(state_file, new_data):
    """Update application state atomically."""
    with safer.open(state_file, 'w') as f:
        new_data['last_updated'] = datetime.now().isoformat()
        json.dump(new_data, f, indent=2)
    # If crash during write, original state file is preserved

What I Learned

After migrating my codebase:

Check maintenance status before adopting libraries - A quick GitHub check would have saved me time
Simpler APIs are better - safer’s open() is more intuitive than atomicwrites’ atomic_write(path, overwrite=True)
Stream support matters - Even if you don’t need it now, you might later
Deprecation warnings are not suggestions - They’re technical debt accumulating

Bottom Line

For new Python projects requiring atomic file writes, use safer. It’s actively maintained, has a cleaner API, and supports streams. If you have existing code using atomicwrites, plan your migration soon.

The library you choose today will be the dependency problem you debug tomorrow. Choose wisely.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

👨‍💻 safer - Python library for writing files safely
👨‍💻 atomicwrites - Atomic file writes (deprecated)
👨‍💻 Reddit discussion: safer vs atomicwrites

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!