Skip to main content

Object Record Table - a CSV like structured data format with native object and array support.

Project description

Object Record Table (ORT)

ORT is a CSV-like structured data format with native support for objects and arrays.
Unlike inefficient human-readable data structures, ORT efficiently represents data, making it ideal for large language model (LLM) token optimization and structured data interchange.

[!TIP] ORT was inspired by Token-Oriented Object Notation (TOON) and was created to contribute to the open-source ecosystem and the advancement of LLMs.
Thank you, TOON.


Table of Contents


Why ORT

Standard JSON and YAML prioritize human readability, but their structural characteristics introduce significant computational overhead when passing data to large language models. ORT addresses this by optimizing data representation for token efficiency.

JSON

{
  "users": [
    {
      "id": 1,
      "profile": {
        "name": "John Doe",
        "age": 30,
        "address": {
          "city": "New York",
          "country": "USA"
        }
      }
    },
    {
      "id": 2,
      "profile": {
        "name": "Jane Smith",
        "age": 25,
        "address": {
          "city": "London",
          "country": "UK"
        }
      }
    }
  ]
}

398 Characters / 118 Tokens

Compact-JSON

{"users":[{"id":1,"profile":{"name":"John Doe","age":30,"address":{"city":"New York","country":"USA"}}},{"id":2,"profile":{"name":"Jane Smith","age":25,"address":{"city":"London","country":"UK"}}}]}

198 Characters / 58 Tokens

ORT

users:id,profile(name,age,address(city,country)):
1,(John Doe,30,(New York,USA))
2,(Jane Smith,25,(London,UK))

110 Characters / 35 Tokens


When Not to Use ORT

ORT is not always the optimal choice. Consider using JSON in the following scenarios:

  • Non-uniform data structures: ORT operates efficiently and reliably with uniform data structures. For heterogeneous data, JSON is more efficient and prevents data loss.
  • Direct application data files: ORT is not optimized for direct input/output operations. Since ORT specializes in data transformation and processing, using JSON for application data files offers better compatibility and stability.

Command-Line Tools

The Rust implementation provides CLI utilities for converting between ORT and JSON formats:

Installation

cargo install ort-rs

Usage

ort2json <input_file>
json2ort <input_file>

# Or with output file specification

ort2json <input_file> -o <output_file>
json2ort <input_file> -o <output_file>

Installation & Usage

PLAYGROUND

ORT Playground

Rust Library

Add to your Cargo.toml:

[dependencies]
ort-rs = "1.0.1"

TypeScript Library

npm i ort-ts

Python Library

pip install ort-python

Package Links


License

This project is licensed under the MIT License. See the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ort_python-1.0.1.tar.gz (10.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ort_python-1.0.1-py3-none-any.whl (10.0 kB view details)

Uploaded Python 3

File details

Details for the file ort_python-1.0.1.tar.gz.

File metadata

  • Download URL: ort_python-1.0.1.tar.gz
  • Upload date:
  • Size: 10.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for ort_python-1.0.1.tar.gz
Algorithm Hash digest
SHA256 69e38ed743414ade6a9cff2c74900d08a070ef8851e082034b59c7db62a097a4
MD5 5da2f9e8de86a4f812dc1132699cda30
BLAKE2b-256 b266ab46c9b4f69b2855e1f31f5e2912126956883150fd75999cc51bf779bd67

See more details on using hashes here.

File details

Details for the file ort_python-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: ort_python-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 10.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.9

File hashes

Hashes for ort_python-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 51fecf42aa690c52fcfa1929a6759f0421a12693dfb8a99219c6efa0109a4970
MD5 4c7774663c34591a13c90f32aac2f146
BLAKE2b-256 0013c24ad188d74acf0140a17c09b1ad0781665f47a10d3f20ae6401780f34a0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page