Mantaray data structure in Python
With this package you can manipulate and interpret mantaray data via MantarayNode
and MantarayFork
abstractions.
- Install using
pip
pip install mantaray_py
from mantaray_py import MantarayNode, MantarayFork, init_manifest_node, gen_32_bytes
node = init_manifest_node()
address1 = gen_32_bytes()
address2 = gen_32_bytes()
address3 = gen_32_bytes()
address4 = gen_32_bytes()
address5 = gen_32_bytes()
address6 = gen_32_bytes()
path1 = "path1/valami/elso".encode()
path2 = "path1/valami/masodik".encode()
path3 = "path1/valami/masodik.ext".encode()
path4 = "path1/valami".encode()
path5 = "path2".encode()
path6 = "path3/haha".encode()
node.add_fork(path1, address1, { "vmi": "elso" })
node.add_fork(path2, address2)
node.add_fork(path3, address3)
node.add_fork(path4, address4, {"vmi": "negy"})
node.add_fork(path5, address5)
node.add_fork(path6, address6, {"vmi": "haha"})
node.remove_path(path3)
print(node)
from mantaray_py import MantarayNode
node = MantarayNode()
"""
here `reference` parameter is a `Reference` type which can be a 32 or 64 of bytes
and `load_function` is a [load_function: (address: bytes): bytes] typed function
that returns the serialised raw data of a MantarayNode of the given reference. See tests/integration/test_int.py file for reference.
"""
node.load(load_function, reference)
# Manipulate `node` object then save it again
# (...)
# save into the storage with a storage handler [save_function: (data: bytes): Reference]
# See tests/integration/test_int.py file for reference.
reference = node.save(save_function)
How It Works
The following describes the format of a node binary format.
┌────────────────────────────────┐
│ obfuscationKey <32 byte> │
├────────────────────────────────┤
│ hash("mantaray:0.1") <31 byte> │
├────────────────────────────────┤
│ refBytesSize <1 byte> │
├────────────────────────────────┤
│ entry <32/64 byte> │
├────────────────────────────────┤
│ forksIndexBytes <32 byte> │
├────────────────────────────────┤
│ ┌────────────────────────────┐ │
│ │ Fork 1 │ │
│ ├────────────────────────────┤ │
│ │ ... │ │
│ ├────────────────────────────┤ │
│ │ Fork N │ │
│ └────────────────────────────┘ │
└────────────────────────────────┘
┌───────────────────┬───────────────────────┬──────────────────┐
│ nodeType <1 byte> │ prefixLength <1 byte> │ prefix <30 byte> │
├───────────────────┴───────────────────────┴──────────────────┤
│ reference <32/64 bytes> │
│ │
└──────────────────────────────────────────────────────────────┘
┌───────────────────┬───────────────────────┬──────────────────┐
│ nodeType <1 byte> │ prefixLength <1 byte> │ prefix <30 byte> │
├───────────────────┴───────────────────────┴──────────────────┤
│ reference <32/64 bytes> │
│ │
├─────────────────────────────┬────────────────────────────────┤
│ metadataBytesSize <2 bytes> │ metadataBytes <varlen> │
├─────────────────────────────┘ │
│ │
└──────────────────────────────────────────────────────────────┘
Documentation: https://Ankvik-Tech-Labs.github.io/mantaray-py/
Source Code: https://github.com/Ankvik-Tech-Labs/mantaray-py
Development
We use Hatch to manage the development environment and production build. Ensure it's installed on your system.
You can run all the tests with:
hatch run test:test
Execute the following command to apply linting and check typing:
hatch run lint:lint-check
You can bump the version, create a commit and associated tag with one command:
hatch version patch
hatch version minor
hatch version major
Your default Git text editor will open so you can add information about the release.
When you push the tag on GitHub, the workflow will automatically publish it on PyPi and a GitHub release will be created as draft.
You can serve the Mkdocs documentation with:
hatch run docs:docs-serve
It'll automatically watch for changes in your code.
This project is licensed under the terms of the BSD 3-Clause License license.