ison-py 1.0.0

ISON (Interchange Simple Object Notation) - A token-efficient data format for AI/LLM workflows

ison-py

ISON (Interchange Simple Object Notation) - A token-efficient data format optimized for AI/LLM workflows.

Features

• 30-70% fewer tokens than JSON for structured data
• ISONL streaming format for fine-tuning datasets and event streams
• Native references for relational data (:-prefixed IDs)
• Type inference for clean, minimal syntax
• Zero dependencies - pure Python implementation

Installation

pip install ison-py

Quick Start

Basic Usage

import ison_parser

# Parse ISON
ison_text = """
table.users
id name email
1 Alice [e-mail]
2 Bob [e-mail]
"""

doc = ison_parser.loads(ison_text)

# Access data
users = doc['users']
print(users.rows[0]['name'])  # Alice

# Convert to JSON
json_data = doc.to_dict()

ISONL Streaming Format

ISONL is perfect for fine-tuning datasets, event streams, and logs:

from ison_parser import loads_isonl, dumps_isonl, isonl_stream

# Parse ISONL
isonl_text = """table.examples|instruction response|"Summarize this" "Brief summary..."
table.examples|instruction response|"Translate to Spanish" "Hola mundo" """

doc = loads_isonl(isonl_text)

# Stream large files (constant memory)
with open("large_dataset.isonl", "r") as f:
    for record in isonl_stream(f):
        process(record)

Format Conversion

from ison_parser import ison_to_isonl, isonl_to_ison

# ISON to ISONL (one line per record)
isonl = ison_to_isonl(ison_text)

# ISONL to ISON (grouped blocks)
ison = isonl_to_ison(isonl_text)

ISON Format

Tables (Structured Data)

table.users
id name email active
1 Alice [e-mail] true
2 Bob [e-mail] false

Objects (Key-Value)

object.config
timeout 30
debug true
api_key "sk-xxx"

References

table.orders
id customer_id total
O1 :C1 99.99
O2 :C2 149.50

ISONL Format

Each line is a self-contained record:

kind.name|field1 field2 field3|value1 value2 value3

Example:

table.users|id name email|1 Alice [e-mail]
table.users|id name email|2 Bob [e-mail]
table.orders|id user total|O1 :1 99.99

Token Efficiency

Records	JSON Tokens	ISON Tokens	Savings
10	~200	~60-140	30-70%
100	~2000	~600-1400	30-70%
1000	~20000	~6000-14000	30-70%

API Reference

Core Functions

• loads(text) - Parse ISON string to Document
• dumps(doc) - Serialize Document to ISON string
• load(path) - Load ISON from file
• dump(doc, path) - Save Document to file

ISONL Functions

• loads_isonl(text) - Parse ISONL string to Document
• dumps_isonl(doc) - Serialize Document to ISONL
• load_isonl(path) - Load ISONL from file
• dump_isonl(doc, path) - Save Document to ISONL file
• isonl_stream(file) - Stream ISONL records (generator)
• ison_to_isonl(text) - Convert ISON to ISONL
• isonl_to_ison(text) - Convert ISONL to ISON

Classes

• Document - Container for ISON blocks
• Block - Single data block (table/object)
• Reference - Reference to another record
• ISONLRecord - Single ISONL record

CLI Usage

# Convert JSON to ISON
ison input.json -o output.ison

# Convert ISON to JSON
ison input.ison --to-json -o output.json

# Validate ISON file
ison input.ison --validate

Database Plugins

Export database tables directly to ISON for LLM workflows:

SQLite (Zero Dependencies)

from ison_parser.plugins import SQLiteToISON

# Export entire database
with SQLiteToISON('mydb.sqlite') as db:
    ison_text = db.export_all()

# Export specific tables
    ison_text = db.export_tables(['users', 'orders'])

# Stream large tables as ISONL
    for line in db.stream_table('logs'):
        print(line)

# Foreign keys auto-convert to ISON references (:id)

PostgreSQL

pip install psycopg2-binary

from ison_parser.plugins import PostgreSQLToISON

with PostgreSQLToISON('postgresql://user:pass@localhost/mydb') as db:
    # Export all tables
    ison_text = db.export_all()

    # Export with related tables (follows foreign keys)
    ison_text = db.export_with_relations('orders')

    # Stream for large datasets
    for line in db.stream_table('events', batch_size=5000):
        process(line)

SQLAlchemy (Any Database)

Works with MySQL, MariaDB, Oracle, MS SQL Server, and more:

pip install sqlalchemy pymysql  # For MySQL

from ison_parser.plugins import SQLAlchemyToISON

# MySQL
with SQLAlchemyToISON('mysql+pymysql://user:pass@localhost/db') as db:
    ison_text = db.export_all()

# Export ORM models directly
from myapp.models import User, Order
    ison_text = db.export_models([User, Order], session)

# Custom queries
    ison_text = db.export_query(
        "SELECT * FROM users WHERE active = true",
        block_name="active_users"
    )

Vector Database Plugins

Export vector search results directly to ISON for RAG pipelines:

ChromaDB

pip install chromadb

from ison_parser.plugins import ChromaToISON

with ChromaToISON() as db:
    # Export RAG context (optimized for LLM prompts)
    ison_context = db.export_for_rag(
        collection='documents',
        query='What is ISON?',
        n_results=5
    )

    # Export search results with scores
    ison_text = db.export_query_results(
        collection='documents',
        query_texts=['semantic search query'],
        n_results=10
    )

    # Stream large collections as ISONL
    for line in db.stream_collection('documents'):
        process(line)

Pinecone

pip install pinecone-client

from ison_parser.plugins import PineconeToISON

exporter = PineconeToISON(api_key='your-key')

# Export search results
ison_text = exporter.export_query_results(
    index='my-index',
    query_vector=embedding,
    top_k=10
)

# RAG context with custom embedding function
ison_context = exporter.export_for_rag(
    index='my-index',
    query='What is ISON?',
    embedding_fn=my_embed_function,
    top_k=5
)

Qdrant

pip install qdrant-client

from ison_parser.plugins import QdrantToISON

exporter = QdrantToISON(host='localhost', port=6333)

# Export search results
ison_text = exporter.export_search_results(
    collection='documents',
    query_vector=embedding,
    limit=10
)

# RAG context
ison_context = exporter.export_for_rag(
    collection='documents',
    query='What is ISON?',
    embedding_fn=my_embed_function,
    limit=5
)

LLM Framework Integrations

Native integrations for major LLM frameworks, providing 30-70% token savings.

LangChain

from ison_parser.integrations import ISONOutputParser

parser = ISONOutputParser()
prompt = f"List users. {parser.get_format_instructions()}"
doc = parser.parse(llm.predict(prompt))

LlamaIndex

from ison_parser.integrations import ISONReader

reader = ISONReader()
documents = reader.load_data("data.ison")
index = VectorStoreIndex.from_documents(documents)

MCP Server (for AI Assistants like Claude)

# Run ISON MCP server
python -m ison_parser.integrations.mcp_server

from ison_parser.integrations import ISONMCPServer, ISONMCPClient

# Server exposes: parse_ison, format_ison, validate_ison, query_ison
server = ISONMCPServer()

# Client with local fallback
async with ISONMCPClient() as client:
    result = await client.parse_ison(ison_text)

OpenAI Function Calling

from ison_parser.integrations import OpenAIISONTools

tools = OpenAIISONTools()
response = client.chat.completions.create(
    model="gpt-4",
    messages=messages,
    tools=tools.get_tool_definitions()
)
doc = tools.parse_response(response)

Anthropic Tool Use

from ison_parser.integrations import AnthropicISONTools

tools = AnthropicISONTools()
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    messages=messages,
    tools=tools.get_tool_definitions()
)
doc = tools.parse_response(response)

Use Cases

• LLM Fine-tuning datasets - 30-70% smaller training files
• RAG pipelines - Token-efficient context from vector DBs
• Database-to-LLM - Direct export with SQL plugins
• Vector search - Export results in compact format
• Event streaming - Append-only logs
• Configuration - Human-readable configs
• API responses - Reduced bandwidth
• MCP Tools - AI assistant integrations

Test Results

All tests passing:

============================= test session starts =============================
platform win32 -- Python 3.12.7, pytest-8.4.1

tests/test_ison_parser.py::test_basic_table PASSED
tests/test_ison_parser.py::test_quoted_strings PASSED
tests/test_ison_parser.py::test_escape_sequences PASSED
tests/test_ison_parser.py::test_type_inference PASSED
tests/test_ison_parser.py::test_references PASSED
tests/test_ison_parser.py::test_null_handling PASSED
tests/test_ison_parser.py::test_dot_path_fields PASSED
tests/test_ison_parser.py::test_comments PASSED
tests/test_ison_parser.py::test_multiple_blocks PASSED
tests/test_ison_parser.py::test_serialization_roundtrip PASSED
tests/test_ison_parser.py::test_to_json PASSED
tests/test_ison_parser.py::test_from_dict PASSED
tests/test_ison_parser.py::test_error_handling PASSED
tests/test_ison_parser.py::test_complete_example PASSED
tests/test_ison_parser.py::test_typed_fields PASSED
tests/test_ison_parser.py::test_relationship_references PASSED
tests/test_ison_parser.py::test_summary_rows PASSED
tests/test_ison_parser.py::test_computed_fields PASSED
tests/test_ison_parser.py::test_serialization_with_types PASSED
tests/test_ison_parser.py::test_isonl_basic_parsing PASSED
tests/test_ison_parser.py::test_isonl_type_inference PASSED
tests/test_ison_parser.py::test_isonl_references PASSED
tests/test_ison_parser.py::test_isonl_multiple_blocks PASSED
tests/test_ison_parser.py::test_isonl_comments_and_empty PASSED
tests/test_ison_parser.py::test_isonl_serialization PASSED
tests/test_ison_parser.py::test_isonl_roundtrip PASSED
tests/test_ison_parser.py::test_ison_to_isonl_conversion PASSED
tests/test_ison_parser.py::test_isonl_to_ison_conversion PASSED
tests/test_ison_parser.py::test_isonl_quoted_pipes PASSED
tests/test_ison_parser.py::test_isonl_error_handling PASSED
tests/test_ison_parser.py::test_isonl_fine_tuning_format PASSED

============================= 31 passed in 0.10s ==============================

Run tests with:

pytest tests/

Links

• Documentation | www.getison.com
• Specification
• ISONL Spec
• GitHub

License

MIT License - see LICENSE for details.