devicer.py 1.5.0

Open-Source Python Middleware for Digital Fingerprinting

FP-Devicer

Developed by Gateway Corporate Solutions LLC

FP-Devicer is a digital fingerprinting middleware library designed for ease of use and near-universal compatibility with servers.

Usage

Importing and using the library to compare fingerprints between users is as simple as collecting user data and running a confidence calculation.

# 1. Simple method (using defaults)
from devicer import calculate_confidence

score = calculate_confidence(fp_data_1, fp_data_2)

# 2. Advanced method (custom weights & comparators)
from devicer import ComparisonOptions, create_confidence_calculator, register_plugin
from devicer.libs.comparators import levenshtein_similarity

register_plugin(
  "userAgent",
  weight=25,
  comparator=lambda a, b, _path=None: levenshtein_similarity(
    str(a or "").lower(),
    str(b or "").lower(),
  ),
)

advanced_calculator = create_confidence_calculator(
  ComparisonOptions(
    weights={
      "platform": 20,
      "fonts": 20,
      "screen": 15,
    },
  )
)

advanced_score = advanced_calculator.calculate_confidence(fp_data_1, fp_data_2)

For storage-backed identification flows:

import asyncio
from devicer import DeviceManager, create_in_memory_adapter


async def main() -> None:
  adapter = create_in_memory_adapter()
  await adapter.init()
  manager = DeviceManager(adapter)

  result = await manager.identify(
    {
      "userAgent": "Mozilla/5.0",
      "platform": "Linux x86_64",
      "languages": ["en-US", "en"],
    },
    user_id="user-1",
    ip="127.0.0.1",
  )
  print(result)  # -> IdentifyResult(device_id=..., confidence=..., is_new_device=...)


asyncio.run(main())

The resulting confidence ranges between 0 and 100, where 100 is the strongest match.

Quickstart

Install and run the Python package:

pip install devicer.py
python -c "from devicer import calculate_confidence; print(calculate_confidence({'platform':'Win32'},{'platform':'Win32'}))"

For local development:

pip install -e .[dev]
pytest -q

Adapters

Built-in adapters:

• create_in_memory_adapter()
• create_sqlite_adapter(path)
• create_postgres_adapter(dsn) (requires optional postgres extras)
• create_redis_adapter(url) (requires optional redis extras)

Install optional adapter dependencies:

pip install -e .[postgres]
pip install -e .[redis]

Benchmarks

You can run benchmark parity scripts for performance and accuracy:

python -m devicer.benchmarks.performance_bench
python -m devicer.benchmarks.accuracy_bench

Outputs are written to:

• src/devicer/benchmarks/performance.bench.out
• src/devicer/benchmarks/accuracy.bench.out

Documentation

The TypeScript SDK documentation is available at gatewaycorporate.github.io/fp-devicer. The Python package mirrors the same core architecture (core, libs, benchmarks, and types) with Pythonic APIs.

Whitepaper

The whitepaper covers the theory, architecture, and design decisions behind FP-Devicer. You can read it here.