What are the differences between json and simplejson Python modules?

python

json-vs-simplejson

python-modules

performance-optimization

byAlex Kataev·Mar 10, 2025

The built-in json module in Python's standard library can be behind in features compared to simplejson, which is updated frequently. In essence, simplejson tends to have newer features and performance improvements before json gets them. For bleeding-edge JSON manipulation, use simplejson.

Both modules work in a similar way:

import json  # or 'import simplejson as json' - the freshest choice from the JSON aisle
data = '{"name": "John", "age": 30}'  # Didn't expect John to be so young, did you?
person = json.loads(data)  # Voila! JSON string is now a Python dictionary!

The script above converts a JSON string into a Python dictionary, regardless of whether you use json or simplejson.

When do I take simplejson out for a spin instead of json?

If your code still has playdates with Python 2.4+, or needs to chummy up with the latest JSON specs and performance boosters, you might want to get your hands on simplejson. Its active attention guarantees you don't miss out on the latest JSON tidbits.

Tweaking your encode-decode shenanigans

simplejson offers additional parameters that help you tweak JSON serialization behavior. For instance:

ignore_nan: Makes sure that out-of-bounds float values (NaN, inf, -inf, or as I like to call them - the naughty floats) don't find their way into serialization.
namedtuple_as_object: Dictates whether namedtuple instances put on their JSON objects disguise or not.

These controls dial in on JSON's versatility in handling various data types.

Talking speed in webspace

When latency feels like a stalker in your graceful dance of web services, simplejson usually flexes its muscles and outperforms json in loads (decoding) and dumps (encoding) operations. But, like choosing the right socks on a chilly night, it's case-specific. Some benchmarks, like the one at http://pastie.org/1507411, suggest that the json module can sometimes cross the tape first. It's all about how preparatory your program’s specific needs are.

What's beyond json and simplejson?

If you're all about squeezing every nanosecond, you might want to give ujson a shot. It’s the "need for speed" contender amongst JSON libraries. Just bear in mind it might play hard to get with some of the additional features that simplejson loves to show off.

One instance, many representations

Pay close attention to how different libraries view the world. For instance, simplejson could serialize a namedtuple instance one way unless you tell it otherwise using namedtuple_as_object=False. These subtleties can lead to differences in perspective, a key thing to remember when you're playing with data exchange between systems.

Regular updates and having a backup plan

Giving simplejson a seat at the table for your project could turn out to be a strategic choice for you. It’s like wearing a belt and suspenders at the same time. Frequent updates mean you have dibs on the latest JSON processing abilities. Plus, you can import simplejson as json to keep your code jogging with newer features and still play nice with older versions.

In it for the long haul

If stability and support over an extensive period give your electrons a buzz, or if you're navigating through the enterprise sphere, you might prefer the standard json module. Although simplejson fills in the potholes for older versions, if you're on board with standardization, you might want to keep things in-house with json.

Making an educated choice

You should turn the json vs. simplejson conundrum on its head based on your project's needs. If efficiency is your goal and you're working with recent Python versions, it might be worth running your use cases through some benchmarks and declaring a winner. If, however, compatibility and conformity rule your world, the default json module could be the rock to your roll.