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ISCC - Codec & Algorithms#

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iscc-core is a Python library that implements the core algorithms of the ISCC (International Standard Content Code)

What is an ISCC#

The ISCC is a similarity preserving identifier for digital media assets.

ISCCs are generated algorithmically from digital content, just like cryptographic hashes. However, instead of using a single cryptographic hash function to identify data only, the ISCC uses various algorithms to create a composite identifier that exhibits similarity-preserving properties (soft hash).

The component-based structure of the ISCC identifies content at multiple levels of abstraction. Each component is self-describing, modular, and can be used separately or with others to aid in various content identification tasks. The algorithmic design supports content deduplication, database synchronization, indexing, integrity verification, timestamping, versioning, data provenance, similarity clustering, anomaly detection, usage tracking, allocation of royalties, fact-checking and general digital asset management use-cases.

What is iscc-core#

iscc-core is the python based library of the core algorithms to create standard-compliant ISCC codes. It also serves as a reference for porting ISCC to other programming languages.


This is a low level reference implementation. iscc-core does not support mediatype detection, metadata extraction or file format specific content extraction. For easy generation of ISCC codes see: iscc-cli

ISCC Architecture#

ISCC Architecture ISCC Architecture

ISCC MainTypes#

Idx Slug Bits Purpose
0 META 0000 Match on metadata similarity
1 SEMANTIC 0001 Match on semantic content similarity
2 CONTENT 0010 Match on perceptual content similarity
3 DATA 0011 Match on data similarity
4 INSTANCE 0100 Match on data identity
5 ISCC 0101 Composite of two or more components with common header
6 ID 0110 Short unique identifier bound to ISCC, timestamp, pubkey
7 FLAKE 0111 Unique time, randomness and counter based distributed ID


Use the package manager pip to install iscc-core.

pip install iscc-core

Quick Start#

import json
import iscc_core as ic

meta_code = ic.gen_meta_code(name="ISCC Test Document!")

print(f"Meta-Code:     {meta_code['iscc']}")
print(f"Structure:     {ic.iscc_explain(meta_code['iscc'])}\n")

# Extract text from file
with open("demo.txt", "rt", encoding="utf-8") as stream:
    text =
    text_code = ic.gen_text_code_v0(text)
    print(f"Text-Code:     {text_code['iscc']}")
    print(f"Structure:     {ic.iscc_explain(text_code['iscc'])}\n")

# Process raw bytes of textfile
with open("demo.txt", "rb") as stream:
    data_code = ic.gen_data_code(stream)
    print(f"Data-Code:     {data_code['iscc']}")
    print(f"Structure:     {ic.iscc_explain(data_code['iscc'])}\n")
    instance_code = ic.gen_instance_code(stream)
    print(f"Instance-Code: {instance_code['iscc']}")
    print(f"Structure:     {ic.iscc_explain(instance_code['iscc'])}\n")

# Compbine ISCC-UNITs into ISCC-CODE
iscc_code = ic.gen_iscc_code(
    (meta_code["iscc"], text_code["iscc"], data_code["iscc"], instance_code["iscc"])

# Create convenience `Code` object from ISCC string
iscc_obj = ic.Code(iscc_code["iscc"])
print(f"ISCC-CODE:     {ic.iscc_normalize(iscc_obj.code)}")
print(f"Structure:     {iscc_obj.explain}")
print(f"Multiformat:   {iscc_obj.mf_base32}\n")

# Compare with random ISCC-CODE:
rand_iscc = ic.Code.rnd(mt=ic.MT.ISCC, bits=256)
print(f"Compare ISCC-CODES:\n{iscc_obj.uri}\n{rand_iscc.uri}")
print(json.dumps(ic.iscc_compare(iscc_obj.code, rand_iscc.code), indent=2))

# Generate an ISCC-ID
iscc_id = ic.gen_iscc_id(iscc_obj.code, chain_id=1, wallet="1Bq568oLhi5HvdgC6rcBSGmu4G3FeAntCz")
iscc_id_obj = ic.Code(iscc_id["iscc"])
print("\nConstruct ISCC-ID:")
print(f"ISCC-ID:       {ic.iscc_normalize(iscc_id_obj.code)}")
print(f"Structure:     {iscc_id_obj.explain}")
print(f"Multiformat:   {iscc_id_obj.mf_base32}")

The output of this example is as follows:

Meta-Code:     ISCC:AAAT4EBWK27737D2
Structure:     META-NONE-V0-64-3e103656bffdfc7a

Text-Code:     ISCC:EAAQMBEYQF6457DP
Structure:     CONTENT-TEXT-V0-64-060498817dcefc6f

Structure:     DATA-NONE-V0-64-fa258b1dcef791a6

Instance-Code: ISCC:IAA3Y7HR2FEZCU4N
Structure:     INSTANCE-NONE-V0-64-bc7cf1d14991538d

Structure:     ISCC-TEXT-V0-MCDI-3e103656bffdfc7a060498817dcefc6ffa258b1dcef791a6bc7cf1d14991538d
Multiformat:   bzqavabj6ca3fnp757r5ambeyqf6457dp7isywhoo66i2npd46hiutektru

  "meta_dist": 37,
  "data_dist": 39,
  "instance_match": false

Construct ISCC-ID:
Structure:     ID-BITCOIN-V0-64-9a741713dc8760ab
Multiformat:   bzqawcae2oqlrhxehmcvq


Project Status#

The ISCC has been accepted by ISO as full work item ISO/AWI 24138 - International Standard Content Code and is currently being standardized at TC 46/SC 9/WG 18.


The iscc-core library and the accompanying documentation is under development. API changes and other backward incompatible changes are to be expected until the upcoming v1.5 stable release.




Pull requests are welcome. For significant changes, please open an issue first to discuss your plans. Please make sure to update tests as appropriate.

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