Registry / aws / dynamo-json

dynamo-json

library1.2.0pypypi✓ verified 84d ago

dynamo-json is a Python utility library (currently v1.2.0) designed to facilitate seamless conversion between standard Python objects (including Decimal, datetime, and UUID) and the specialized JSON format used by Amazon DynamoDB. It provides `dumps` and `loads` functions that mimic the standard `json` library, handling the DynamoDB type descriptors (e.g., {'S': 'string'}, {'N': '123'}) automatically. The library has been in maintenance mode since its last update in 2020, with a focus on stable functionality.

aws serialization database

pip install dynamo-json

github ↗package ↗

INSTALL

IMPORT

SIG · DYNAMO-JSON

dynamo-json

awspythonv1.2.0

Install

1.7s avg

Import

—

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.2.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 17.8MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 1.7s · import 0.000s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

json

✓ from dynamo_json import json

✗ from dynamo_json import json_util as json

marshall

✓ from dynamo_json import marshall

unmarshall

✓ from dynamo_json import unmarshall

Demonstrates converting a complex Python dictionary containing Decimals, datetimes, and UUIDs to DynamoDB-compatible JSON and back. The `json_util` module handles the necessary type marshalling and unmarshalling.

import time import uuid from datetime import datetime from decimal import Decimal from dynamo_json import json_util as json # Python object with various types, including those requiring special handling by DynamoDB json_ = { "MyString": "a", "num": 4, "MyBool": False, "my_dict": {"my_date": datetime.now(), "my_uuid": uuid.uuid4()}, "MyList": [Decimal('1.23'), 2, 3], "MyNull": None } # Convert Python object to DynamoDB JSON format dynamo_json_data = json.dumps(json_) print("DynamoDB JSON:\n", dynamo_json_data) # Convert DynamoDB JSON format back to a Python object python_object = json.loads(dynamo_json_data) print("Python object:\n", python_object)

Debug

Known issues

gotchaThere is a similarly named but distinct library called `dynamodb-json` (with 'db') developed by Alonreznik, which also provides DynamoDB JSON conversion functionalities and uses a very similar import pattern (`from dynamodb_json import json_util as json`). Ensure you install `dynamo-json` (`pip install dynamo-json`) if you intend to use this specific library by adilosa, to avoid unexpected behavior or missing features from the wrong package.

fix

Always explicitly install `dynamo-json` if this specific library is desired, and verify the package source if encountering unexpected behavior.

affects: All

gotchaDynamoDB has a strict item size limit of 400KB. While `dynamo-json` handles the format conversion, it does not bypass this underlying DynamoDB constraint. Attempting to serialize very large Python objects will result in DynamoDB errors when `put_item` is called.

fix

For items exceeding 400KB, consider storing large attributes in Amazon S3 and referencing them in DynamoDB, or restructure your data model to break down large items into smaller ones.

affects: All

gotchaDynamoDB supports high-precision numbers (up to 38 digits) which are typically represented as strings in DynamoDB JSON (`{'N': '123.45'}`). This library correctly handles `Decimal` objects. If you process data outside of `dynamo-json`'s `dumps`/`loads` using standard JSON libraries, you might lose precision for large numbers or encounter `TypeError` for `Decimal` objects.

fix

Consistently use `dynamo_json.json_util.dumps()` and `loads()` for all DynamoDB-related JSON serialization/deserialization to ensure proper handling of numerical precision and other complex types like `datetime` and `UUID`.

affects: All

Upgrade

Version history

1.2.0latest on PyPI · released Jun 30, 2020

Audit

Dependencies

No dependency data recorded yet.

Agent activity

23 hits · last 30 days

node

Amazon

Resources

githubhttps://github.com/adilosa/dynamo-json ↗

packagehttps://pypi.org/project/dynamo-json/ ↗