CDXF — Compact Data Exchange Format

A universal binary interchange format whose information model is a provable superset of JSON, YAML, XML, and TOML, enabling lossless round-trip encoding of documents from any of these format families.

Status

Alpha. The specification and reference implementation are functional with 408 tests passing. All four format bridges (JSON, YAML, XML, TOML) are complete with full round-trip fidelity verified on a 43-file benchmark corpus.

Motivation

Every existing binary serialization format is anchored to a single text format's information model. CBOR and MessagePack encode the JSON data model. EXI and Fast Infoset encode the XML Information Set. Nothing encodes YAML's graph-structured representation or TOML's typed configuration model. And critically, no binary format preserves all of them through a single unified information model.

CDXF fills that gap.

What CDXF preserves that others lose

Empirically verified via automated tests (EXP-001 Feature Preservation Matrix):

Installation

pip install cdxf

CLI Usage

# Encode a JSON file to CDXF binary
cdxf encode config.json                   # -> config.cdxf

# Decode back to text (auto-detects source format)
cdxf decode config.cdxf                   # -> config.json

# Convert between formats via CDXF
cdxf convert data.yaml --to json          # -> data.json
cdxf convert config.json --to toml        # -> config.toml

# Inspect a file
cdxf info config.json
# File:          config.json
# Type:          JSON text
# Text size:     2,946 bytes
# CDXF size:     2,001 bytes
# Ratio:         0.679
# Node counts:   {'Map': 9, 'Scalar': 114, 'Sequence': 2}

Python API

from cdxf.bridges import from_json, to_json, from_yaml, to_yaml
from cdxf.bridges import from_xml, to_xml, from_toml, to_toml
from cdxf.codec import encode, decode

# JSON round-trip through binary
stream = from_json('{"name": "Alice", "age": 30}')
binary = encode(stream)          # compact CBOR-based binary
restored = decode(binary)
print(to_json(restored))         # '{"name": "Alice", "age": 30}'

# Cross-format conversion: YAML → CDXF → JSON
stream = from_yaml("name: Alice\nage: 30\n")
print(to_json(stream))           # '{"name": "Alice", "age": 30}'

# YAML with anchors and comments — preserved through binary
yaml_doc = """
# Server defaults
defaults: &defaults
  timeout: 30
  retries: 3
production:
  <<: *defaults
  timeout: 60
"""
stream = from_yaml(yaml_doc)
binary = encode(stream)          # anchors, comments, merge keys preserved
restored = decode(binary)
print(to_yaml(restored))         # anchors and comments survive

# XML with namespaces and mixed content
xml_doc = '<p xmlns="http://www.w3.org/1999/xhtml">Hello <b>world</b>!</p>'
stream = from_xml(xml_doc)
binary = encode(stream)          # namespaces, mixed content preserved
restored = decode(binary)
print(to_xml(restored))          # faithful reconstruction

Size Efficiency

Median CDXF/text size ratios on a 43-file benchmark corpus:

For JSON data, CDXF shorthand mode produces byte-identical output to standard CBOR — zero overhead.

Documentation

• docs/information_model.md — Formal specification: 9 node kinds, 2 conformance levels, format mapping proofs
• docs/binary_encoding.md — CBOR-based wire format with 16 semantic tags
• docs/literature_survey_universal_binary_interchange.md — Comprehensive gap analysis of existing binary formats

License

MIT. See LICENSE.

Author

Muntaser Syed (@jemsbhai) — Florida Institute of Technology