laga 0.1.5

Repair malformed JSON from language models and hand-written config.

laga

laga repairs malformed JSON and returns Python objects.

It is built for the real world: model output, hand-written config, copied snippets, and other almost-JSON text that is usually close enough to recover but not strict enough for json.loads.

Highlights

• Repairs common JSON mistakes such as trailing commas, missing commas, single quotes, unquoted keys, comments, fences, smart quotes, and truncated containers.
• Tries the standard library first, so valid JSON stays fast and strict.
• Keeps the public API small: repair, repair_to_str, loads, and LagaError.
• Ships with a CLI, type information, tests, docs, and CI.

Supported Versions

laga 0.1.5 supports Python 3.10 through 3.13.

Install

For normal use from PyPI:

python -m pip install laga

For local development from a checkout:

python -m pip install -e ".[dev]"

Quick Start

import laga

text = "{name: 'Ada', active: True, roles: ['admin', 'writer',],}"

data = laga.repair(text)
print(data)
print(laga.repair_to_str(text))

CLI

You can also use laga from the command line:

laga "{name: 'Ada', active: True, roles: ['admin',]}"
laga --strict '{"a": 1,}'

Use --strict when you want to reject ambiguous repairs instead of filling in gaps. Use --pretty to format output for humans, --stdin to read from standard input, and --duplicate-keys error when duplicate keys should fail. Use --input to read from a file and --output to write the repaired result back to disk.

laga --stdin --pretty
laga --input sample.txt --output fixed.json
laga --max-depth 64 --max-input-size 10000 --duplicate-keys error '{"a": 1}'

API

Function	Returns	Description
laga.repair(text, strict=False)	Python object	Repairs malformed JSON and returns Python data.
laga.repair_to_str(text, strict=False)	str	Repairs malformed JSON and returns normalized JSON text.
laga.repair_file(path, strict=False)	Python object	Reads a file and repairs its contents.
laga.loads(text, strict=False)	Python object	Alias for laga.repair.
laga.LagaError	Exception type	Raised when repair fails or input is unrecoverable.

What It Repairs

Rule	Before	After
Trailing comma	{"a": 1,}	{"a":1}
Missing comma	{"a": 1 "b": 2}	{"a":1,"b":2}
Single quotes	{'a': 'b'}	{"a":"b"}
Unquoted keys	{name: "Ada"}	{"name":"Ada"}
Python literals	{"ok": True, "none": None}	{"ok":true,"none":null}
Comments	{"a": 1 // note\n}	{"a":1}
Markdown fences	json\n{"a":1}\n	{"a":1}
Smart quotes	“a”	"a"
Prose around JSON	Result: {"a":1}	{"a":1}
Truncated structure	{"a": [1, 2	{"a":[1,2]}

Strict Mode

strict=True is for validation workflows where you want laga to fail instead of guessing.

In strict mode, laga rejects ambiguous recoveries such as:

• missing commas between object members or array items
• unterminated objects or arrays
• other repairs that would require filling in structure the input did not clearly provide

Behavior Notes

• json.loads is still the best choice when you control the producer and the input is already valid JSON.
• Duplicate keys use last-value-wins behavior, matching Python dict semantics.
• Use duplicate_keys="error" when you want duplicate object members to fail instead of being merged.
• laga does not evaluate expressions or try to invent arbitrary JavaScript syntax.
• The parser is intentionally conservative around malformed numbers and highly ambiguous text.

Quick Decision Guide

Situation	Best choice
You control the producer and the input is valid JSON	json.loads
You have noisy LLM output, copied config, or prose around JSON	laga.repair
You need to repair a file directly	laga.repair_file
You want duplicate keys to fail	duplicate_keys="error"
You want a human-friendly result	repair_to_str(..., pretty=True)

When To Use laga

Use laga when the input is noisy, user-facing, or generated by a model and you need a predictable repair step before parsing.

Use json.loads when correctness and strictness matter more than recovery.

Development

make install
make lint
make typecheck
make test
make build

Project Links

• Documentation: docs/index.md
• API details: docs/api.md
• Usage examples: docs/usage.md
• Contributing guide: CONTRIBUTING.md

Citation

If you use laga in academic work, research notes, or other formal writing, please cite the repository using the metadata in CITATION.cff.

Suggested citation format:

Laitinen-Fredriksson Lundström-Imanov, G. O. Y. (2026). laga (Version 0.1.5) [Computer software]. https://github.com/olaflaitinen/laga