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ISCC - Codec & Algorithms#

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iscc-core is the reference implementation of the core algorithms of the ISCC (International Standard Content Code)

What is the ISCC#

The ISCC is a similarity preserving fingerprint and 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 a python based reference library of the core algorithms to create standard-compliant ISCC codes. It also a good reference for porting ISCC to other programming languages.


This is a low level reference implementation that does not inlcude features like mediatype detection, metadata extraction or file format specific content extraction. Please have a look at the iscc-sdk which adds those higher level features on top of the iscc-core library.

Project Status#

The ISCC is under development as ISO/CD 24138 - International Standard Content Code within ISO/TC 46/SC 9/WG 18.

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


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")

# Combine 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 changed ISCC-CODE:
new_dc, new_ic = ic.Code.rnd(mt=ic.MT.DATA), ic.Code.rnd(mt=ic.MT.INSTANCE)
new_iscc = ic.gen_iscc_code((meta_code["iscc"], text_code["iscc"], new_dc.uri, new_ic.uri))
print(f"Compare ISCC-CODES:\n{iscc_obj.uri}\n{new_iscc['iscc']}")
print(json.dumps(ic.iscc_compare(iscc_obj.code, new_iscc["iscc"]), indent=2))

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": 0,
  "content_dist": 0,
  "data_dist": 33,
  "instance_match": false


Documentation is published at



  • Python 3.7.2 or higher for code generation and static site building.
  • Poetry for installation and dependency management.

Development Setup

git clone
cd iscc-core
poetry install

Development Tasks

Tests, coverage, code formatting and other tasks can be run with the poe command:


Poe the Poet - A task runner that works well with poetry.
version 0.18.1

Result: No task specified.

  poe [-h] [-v | -q] [--root PATH] [--ansi | --no-ansi] task [task arguments]

  -h, --help     Show this help page and exit
  --version      Print the version and exit
  -v, --verbose  Increase command output (repeatable)
  -q, --quiet    Decrease command output (repeatable)
  -d, --dry-run  Print the task contents but don't actually run it
  --root PATH    Specify where to find the pyproject.toml
  --ansi         Force enable ANSI output
  --no-ansi      Force disable ANSI output
  gentests       Generate conformance test data
  format         Code style formating with black
  docs           Copy to /docs
  format-md      Markdown formating with mdformat
  lf             Convert line endings to lf
  test           Run tests with coverage
  sec            Security check with bandit

Use poe all to run all tasks before committing any changes.




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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