Skip to main content

An implementation of the DAG-PB spec for Python.

Project description

ipld-dag-pb

An implementation of the DAG-PB spec for Python.

Install

pip install ipld-dag-pb

Usage

from ipld_dag_pb import PBNode, encode, decode, code
from multiformats import multihash, CID

node = PBNode("Some data as a string".encode("utf-8"))
encoded_bytes = encode(node)

# Alternatively:
# from ipld_dag_pb import prepare
# encoded_bytes = encode(prepare("Some data as a string"))

digest = multihash.digest(encoded_bytes, "sha2-256")
cid = CID("base32", 1, code, digest)

print(str(cid) + " => " + encoded_bytes.hex())
# bafybeibweq2akodv3uezac2g225qvjynh7lv3xv4wp5c4uxfppogtwt3fe => 0a15536f6d652064617461206173206120737472696e67

decoded_bytes = decode(encoded_bytes)
print(decoded_bytes)
print("decoded 'Data': " + bytes(decoded_bytes.data).decode("utf-8"))
# decoded 'Data': Some data as a string

prepare()

The DAG-PB encoding is very strict about the Data Model forms that are passed in. The objects must exactly resemble what they would if they were to undergo a round-trip of encode & decode. Therefore, extraneous or mistyped properties are not acceptable and will be rejected. See the DAG-PB spec for full details of the acceptable schema and additional constraints.

Due to this strictness, a prepare() function is made available which simplifies construction and allows for more flexible input forms. Prior to encoding objects, call prepare() to receive a new object that strictly conforms to the schema.

from ipld_dag_pb import prepare
from multiformats import CID

print(vars(prepare("Some data as a string")))
# -> {'data': b'Some data as a string', 'links': []}
print(vars(prepare({"links": [CID.decode("bafkqabiaaebagba")]})))
# -> {'data': None, 'links': [<ipld_dag_pb.node.PBLink object at 0x102c1b0e0>]}

Contributing

All welcome! storacha.network is open-source.

License

Dual-licensed under Apache-2.0 OR MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ipld_dag_pb-0.0.1.tar.gz (21.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ipld_dag_pb-0.0.1-py3-none-any.whl (12.9 kB view details)

Uploaded Python 3

File details

Details for the file ipld_dag_pb-0.0.1.tar.gz.

File metadata

  • Download URL: ipld_dag_pb-0.0.1.tar.gz
  • Upload date:
  • Size: 21.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for ipld_dag_pb-0.0.1.tar.gz
Algorithm Hash digest
SHA256 e205f613d6a0f4b276bfc2d40f0c07db173a0fd2f938862f867ce05f2eddd417
MD5 0cc1fbb1c401ffd28adaaffd38330566
BLAKE2b-256 73426a6cbb0cab9bd644d561b7f1023b20d8b84cabee739b35f2c473a53e5606

See more details on using hashes here.

File details

Details for the file ipld_dag_pb-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: ipld_dag_pb-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 12.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for ipld_dag_pb-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 fc5fee4bff126571446a4ae5ac8342c05221759f995e7d4ded22ad9df33c8c89
MD5 ca092ea8b08179c2f40c502bcb28c350
BLAKE2b-256 c89c7a042e1b5e54ea807300fd96123767e7251bcd2bd59312ba2e33376bad5f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page