PyFernet (pyfernet-payload)

中文说明

Pack a training source directory into a single .enc blob; on the client, decrypt and run from an in-memory VFS. Only an empty directory tree is created on disk (for Path(__file__) / chdir); .py / config contents are never written. Removed on exit.

• Zero third-party runtime deps (stdlib AES-128-CBC + Fernet-compatible format)
• PyPI name: pyfernet-payload (pyfernet is already taken)
• CLI / import: pyfernet / import pyfernet
• Relative paths work: Path(__file__).parent / "train_config.json", open, spec_from_file_location via VFS hooks

Install

pip install pyfernet-payload

From a local clone:

# preferred on older pip / mirrors (no editable hook needed)
python3 -m pip install .

# or editable (dev); if this fails, upgrade pip first:
python3 -m pip install -U pip setuptools wheel
python3 -m pip install -e .

CLI

Encrypt

pyfernet encrypt ./my_train -o train_payload.enc -e train.py
# passphrase via prompt; or:
export PYFERNET_PASSWORD='your-secret'
pyfernet encrypt ./my_train -o train_payload.enc -e train.py --password-env PYFERNET_PASSWORD

Run

pyfernet run train_payload.enc
# forward args to the training entry (after --):
pyfernet run train_payload.enc -- --epochs 50 --batch 8

Equivalent:

python -m pyfernet encrypt ./my_train -o train_payload.enc -e train.py
python -m pyfernet run train_payload.enc

Workflow

1. Local: write training code → pyfernet encrypt → train_payload.enc
2. SFTP: upload the ciphertext only (client already has pip install pyfernet-payload)
3. SSH: pyfernet run train_payload.enc, enter passphrase
4. Decrypt into memory → empty dir anchors + VFS hooks → start training; write weights to a normal disk path
5. On exit, remove empty dirs; durable disk still has only ciphertext

If the entry uses sibling dirs (e.g. train_detect_rtdetrv2/ + train_detect_cfg/ + train_detect_yolo/), encrypt the parent folder and set -e train_detect_rtdetrv2/train_insect.py.

Inference code, datasets, and weights can stay plaintext on the client.

IDE variable mode (optional)

With no CLI args, modules use the variables at the bottom of the file:

python -m pyfernet.encryptor   # no args → SOURCE_DIR / OUTPUT_PATH / ENTRY_POINT
python -m pyfernet.loader      # no args → PAYLOAD_PATH / TRAIN_ARGV

With args, they use the CLI, e.g. python -m pyfernet.encryptor ./src -o out.enc -e train.py.

Library API

from pyfernet import encrypt_directory, run_payload

encrypt_directory("examples/demo_train", "dist/train_payload.enc", "train.py", "secret")
run_payload("dist/train_payload.enc", "secret", argv=["train.py", "--epochs", "1"])

Payload format

PYFE1\0  +  16B salt  +  Fernet(token)

Fernet plaintext is a zip (sources + _pyfernet_manifest.json). The passphrase is stretched with PBKDF2-HMAC-SHA256 (390000 iterations).

Notes

• Source file bytes never hit disk; only empty directories exist briefly (often under /dev/shm on Linux)
• Process memory / debuggers can still see plaintext; a leaked passphrase decrypts the blob
• By default only .py and a few config suffixes are packed—do not put datasets or weights in the blob
• The client still needs training deps installed (torch, ultralytics, etc.)

Publish to PyPI

See docs/PUBLISH.md (中文).

Layout

PyFernet/
  pyproject.toml
  README.md              # English (PyPI)
  README.zh-CN.md        # Chinese
  src/pyfernet/
    cli.py
    encryptor.py
    loader.py
    fernet_lite.py
  examples/demo_train/
  docs/PUBLISH.md
  docs/PUBLISH.zh-CN.md