Core Library
Main Documentation: https://nes-lab.github.io/shepherd
Source Code: https://github.com/nes-lab/shepherd-tools
Main Project: https://github.com/nes-lab/shepherd
shepherd-core is designed as a library and bundles data-models and file-access-routines for the shepherd-testbed, that are used by several codebases.
For postprocessing shepherds .h5-files usage of shepherd_data is recommended.
Features
- read and write shepherds hdf5-files
- create, read, write and convert experiments for the testbed
- all required data-models are included
- simulate the virtual source, including virtual harvesters (and virtual converter as a whole)
- connect and query the testbed via a webclient (TestbedClient in alpha-stage)
- offline usage defaults to static demo-fixtures loaded from yaml-files in the model-directories
- work with target-firmwares
- embed, modify, verify, convert
- Note: working with ELF-files requires external dependencies, see
Installation-Chapter
- decode waveforms (gpio-state & timestamp) to UART
- create an inventory (for deployed versions of software, hardware)
See official documentation or example scripts for more details and usage. Most functionality is showcased in both. The extra-directory holds data-generators relevant for the testbed. Notably is a trafficbench-experiment that's used to derive the link-matrix of the testbed-nodes.
Config-Models in Detail
These pydantic data-models are used throughout all shepherd interfaces. Users can create an experiment, include their own content and feed it to the testbed.
- orchestration
/data-modelswith focus on remote shepherd-testbed - classes of sub-models
/base: base-classes, configuration and -functionality for all models/testbed: meta-data representation of all testbed-components/content: reusable user-defined meta-data for fw, h5 and vsrc-definitions/experiment: configuration-models including sub-systems/task: digestible configs for shepherd-herd or -sheep- behavior controlled by
ShpModelandcontent-model
- a basic database is available as fixtures through a
tb_client- fixtures selectable by name & ID
- fixtures support inheritance
- the models support
- auto-completion with neutral / sensible values
- complex and custom datatypes (i.e. PositiveInt, lists-checks on length)
- checking of inputs and type-casting
- generate their own schema (for web-forms)
- pre-validation
- store to & load from yaml with typecheck through wrapper
- documentation
- experiment-definition is designed securely
- types are limited in size (str)
- exposes no internal paths
- experiments can be transformed to task-sets (
TestbedTasks.from_xp())
Compatibility
| OS | PyVersion | Comment |
|---|---|---|
| Ubuntu | 3.8 - 3.13 | |
| Windows | 3.8 - 3.13 | no support for elf and hex-conversions yet |
| MacOS | 3.8 - 3.13 | hex-conversion missing |
Notes:
- hex-conversion needs a working and accessible objcopy
- elf-supports needs
shepherd-core[elf]installspwntools-elf-only- most elf-features also still utilize hex-conversion
Installation
The Library is available via PyPI and can be installed with
pip install shepherd-core -U
# or for the full experience (includes core)
pip install shepherd-data -U
For bleeding-edge-features or dev-work it is possible to install directly from GitHub-Sources (here dev-branch):
pip install git+https://github.com/nes-lab/shepherd-tools.git@dev#subdirectory=shepherd_core -U
# and on sheep with newer debian
sudo pip install git+https://github.com/nes-lab/shepherd-tools.git@dev#subdirectory=shepherd_core -U --break-system-packages
If you are working with .elf-files (embedding into experiments) you make "objcopy" accessible to python. In Ubuntu, you can either install build-essential or binutils-$ARCH with arch being msp430 or arm-none-eabi for the nRF52.
sudo apt install build-essential
For more advanced work with .elf-files (modify value of symbols / target-ID) you should install
pip install shepherd-core[elf]
and also make sure the prereqs for the pwntools are met.
For creating an inventory of the host-system you should install
pip install shepherd-core[inventory]
Unittests
To run the testbench, follow these steps:
- Navigate your host-shell into the package-folder and
- install dependencies
- run the testbench (~ 320 tests):
cd shepherd-tools/shepherd_core
pip3 install ./[tests]
pytest
1 maintainer
Metadata
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Release files for shepherd-core 2026.10.1
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