SPaC-Kit

✨ Introduction

SpaC-Kit is a collection of Python tools for working with CCSDS Space Packets. It can generically:

• Parse data files into Pandas DataFrames or Excel spreadsheets
• Generate simulated CCSDS packets with randomized/zero-initialized fields for testing
• Generate automatic documentation for packets with a Sphinx extension

SpaC-Kit supports mission or instrument-specific CCSDS packet structures via plugin packages built on the CCSDSPy library.

🔌 Available Mission/Instrument Plugins

• Europa Clipper CCSDS packet definitions
• Want to define your own CCSDS packets? Open a ticket to start the discussion.

Users

Requirement

Tested with python 3.12.

Optionally, but recommended, create a virtual environment:

python3 -m venv .venv
source .venv/bin/activate

Install

Install your plugin library first, for example Europa-Clipper CCSDS packets definitions:

git clone https://github.com/nasa-jpl/spac-kit-europa-clipper.git
cd spac-kit-europa-clipper
pip install .

Install the SPaC-Kit package:

pip install spac-kit

Use

SPaC-Kit provides three main capabilities for working with CCSDS packets:

1. 📄 Parsing CCSDS Packets (spac-parse)

The spac-parse command parses binary CCSDS packet files and outputs structured data in various formats.

Basic usage:

spac-parse --file {your_ccsds_file}

Output formats:

Export to Excel (default):

spac-parse --file packets.bin --output data.xlsx

Export to CSV:

spac-parse --file packets.bin --format csv --output data.csv

Export to Pandas DataFrame pickle:

spac-parse --file packets.bin --format pickle --output data.pkl

Filtering options:

Parse only specific APID(s):

spac-parse --file packets.bin --apid 100 200 --output filtered.xlsx

Advanced options:

See all available options:

spac-parse --help

Programmatic usage:

from spac_kit.parser import parse_packets

# Parse packets and get DataFrame
df = parse_packets("packets.bin", apids=[100, 200])

# Access parsed data
print(df.head())
print(df["temperature"].mean())

2. 🔧 Generating CCSDS Packets (spac-generate)

The spac-generate command creates simulated CCSDS packets for testing and development.

Basic usage:

Generate packets with random data for all installed packet definitions:

spac-generate --output packets.bin

Data initialization options:

Generate packets with zero-initialized data:

spac-generate --output packets.bin --zeros

Filtering and quantity:

Generate packets for specific APID(s):

spac-generate --output packets.bin --apid 100 200

Generate multiple packets per APID:

spac-generate --output packets.bin --count 10

Listing definitions:

List available packet definitions:

spac-ls

Advanced options:

See all available options:

spac-generate --help

Programmatic usage:

The packet generator creates valid CCSDS packets, useful for testing packet parsing pipelines.

import ccsdspy
from spac_kit.generator import PacketGenerator

# Define packet structure
fields = [
    ccsdspy.PacketField(name="status", data_type="uint", bit_length=8),
    ccsdspy.PacketField(name="temperature", data_type="float", bit_length=32),
]
packet_def = ccsdspy.VariableLength(fields, apid=100, name="SensorPacket")

# Generate packets with random data (default)
generator = PacketGenerator(packet_def)
with open("packets.bin", "wb") as f:
    generator.write_packet(f, count=5)  # Generate 5 packets

# Generate packets with zero-initialized data
with open("zeros.bin", "wb") as f:
    generator.write_packet(f, count=5, use_random=False)

3. 📚 Automatic Documentation (spac-autodocs)

SPaC-Kit includes a Sphinx extension for automatically generating documentation for CCSDS packet definitions.

Setup:

Add to your Sphinx conf.py:

extensions = [
    'spac_kit.sphinx_ext',
    # ... other extensions
]

Usage in documentation:

.. spac-autodocs::
   :apid: 100
   :name: SensorPacket

This will generate formatted documentation including field names, types, bit lengths, and descriptions from your packet definitions.

Developers

Requirements

Python 3.12

Create a virtual environment

SPaC-Kit handles development primarily via Poetry. To setup the repo, run:

poetry env use python3.12
poetry install --with dev

Then prefix your commands with poetry run to use the virtual environment, for example:

poetry run spac-parse --help

Deploy the project, for developers

Clone the repository

Install the package

pre-commit install && pre-commit install -t pre-push

Run an example:

python src/spac_kit/parser/downlink_to_excel.py

or

spac-parse --help

With poetry, update the poetry.lock before commiting and pushing to the github repository:

poetry lock

Build and publish the package

Update the version number in file pyproject.toml

Create a tag in the repository and push the changes.

git tag vX.Y.Z
git push origin main --tags

Locally, you can do the following steps to build and publish the package.

python3 -m pip install --upgrade build
rm -rf dist/
python3 -m build

Publish the project:

pip install twine
twine upload dist/*

Other reference information for developers

• The package is released following Semantic Versioning.
• We follow the trunk-based branching strategy since the development team is current reduced and we want to favor efficient of the releases. That mean we don't have a 'develop' branch.
• The code follows the PEP-8 style guide using black for formatting and flake8 for linting.

Acknowledgments

The work being done here heavily relies on the CCSDSpy library. It has been started as part of the NASA Europa Clipper mission Science Data System development and it is being now funded by a NASA ROSES grant.