activitypubdantic 0.0.3

Pydantic Models for ActivityPub with Classes for Enabling Interactions

ActivityPubdantic

Validate and Interact with ActivityPub JSON

GitHub Repository

ActivityPubdantic Documentation

ActivityPub Protocol

ActivityStreams Specification

What Is ActivityPubdantic?

ActivityPubdantic is a suite of tools for validating ActivityPub JSON and constructing consistent representations of ActivityPub notifications and content. Pydantic models enable the validation logic and can be imported for use in custom-coded classes or FastAPI routes.

Why Does ActivityPub JSON Require Validation?

ActivityPub is a protocol for decentralized social networking. It defines client-to-server and server-to-server interactions and relies on ActivityStreams for its vocabulary. Many of the protocol's specifications are purposefully unrestrictive, giving developers the freedom to implement only the features relevant to their products or to adjust to meet their particular requirements.

However, that flexibility presents challenges for assessing data validity and simplifying developers' code. ActivityPubdantic helps developers overcome those challenges by using ActivityPub's type field to identify proper checks for other fields and standardize their structures. Examples are available in the sections below.

Mastodon supports ActivityPub, and Meta's Threads app plans to conform to the protocol sometime in the near future. ActivityPubdantic includes a pytest script, which uses examples from ActivityPub, ActivityStreams, and Mastodon to test its parsing and validation. As Threads and other platforms implement ActivityPub, those tests (and more broadly, this package) will be updated to stay current.

Installation

Install ActivityPubdantic with pip:

pip install activitypubdantic

Most developer use cases will require one or both of the following import statements, which serve different purposes:

# Use classes for validation and common operations
import activitypubdantic as ap

# Use models in FastAPI routes
from activitypubdantic.models import *

Examples

The following examples include simple use cases and code snippets for ActivityPubdantic. For a more thorough listing of ActivityPubdantic's classes, functions, and models, check out its documentation.

Parsing Activity, Collection, Link, and Object JSON

Activities, Collections, Links, and Objects are the core concepts around which ActivityPub and ActivityStreams are built. By reducing their complexity and standardizing their representation, ActivityPubdantic helps resolve potential pain points for developers.

ActivityPub's protocol includes an example of a Like activity. The example's to field is a list, while its cc field is a string. Both formats are valid, but they require slightly different handling in subsequent lines of code. To resolve that difference, ActivityPubdantic copies and rewrites the JSON, so those fields are always represented as lists of dictionaries.

import activitypubdantic as ap

# Example JSON from ActivityPub documentation
example_json = {
  "@context": ["https://www.w3.org/ns/activitystreams",
               {"@language": "en"}],
  "type": "Like",
  "actor": "https://dustycloud.org/chris/",
  "name": "Chris liked 'Minimal ActivityPub update client'",
  "object": "https://rhiaro.co.uk/2016/05/minimal-activitypub",
  "to": ["https://rhiaro.co.uk/#amy",
         "https://dustycloud.org/followers",
         "https://rhiaro.co.uk/followers/"],
  "cc": "https://e14n.com/evan"
}

# Get the appropriate class, which is determined by the type field
output_class = ap.get_class(example_json)

# Produce the parsed and validated JSON string
output_json = output_class.json()
print(output_json)  # See JSON below

get_class() reads the example_json and uses its type to select the applicable Pydantic model. That model then uses validators for each field to assert they comply with the protocol and then restructures them.

The output_json is longer and, at first glance, more difficult to read. But because it contains types for each item in its fields and it standardizes the structures of similar fields – like to and cc – it is more descriptive and easier to consistently manipulate.

{
  "@context": [
    "https://www.w3.org/ns/activitystreams",
    {
      "@language": "en"
    }
  ],
  "type": "Like",
  "name": "Chris liked 'Minimal ActivityPub update client'",
  "to": [
    {
      "@context": "https://www.w3.org/ns/activitystreams",
      "type": "Object",
      "id": "https://rhiaro.co.uk/#amy"
    },
    {
      "@context": "https://www.w3.org/ns/activitystreams",
      "type": "Object",
      "id": "https://dustycloud.org/followers"
    },
    {
      "@context": "https://www.w3.org/ns/activitystreams",
      "type": "Object",
      "id": "https://rhiaro.co.uk/followers/"
    }
  ],
  "cc": [
    {
      "@context": "https://www.w3.org/ns/activitystreams",
      "type": "Object",
      "id": "https://e14n.com/evan"
    }
  ],
  "actor": [
    {
      "@context": "https://www.w3.org/ns/activitystreams",
      "type": "Object",
      "id": "https://dustycloud.org/chris/"
    }
  ],
  "object": {
    "@context": "https://www.w3.org/ns/activitystreams",
    "type": "Object",
    "id": "https://rhiaro.co.uk/2016/05/minimal-activitypub"
  }
}

However, not every project requires that degree of granularity. For example, some servers may already have logic that ignores additional fields and only iterates through id URLs in the JSON.

# Use the verbose keyword argument
short_output_json = output_class.json(verbose=False)
print(short_output_json)  # See JSON below

Setting verbose=False shortens the output, retaining consistency but eliminating unneeded data for more concise tasks.

{
  "@context": [
    "https://www.w3.org/ns/activitystreams",
    {
      "@language": "en"
    }
  ],
  "type": "Like",
  "name": "Chris liked 'Minimal ActivityPub update client'",
  "to": [
    "https://rhiaro.co.uk/#amy",
    "https://dustycloud.org/followers",
    "https://rhiaro.co.uk/followers/"
  ],
  "cc": ["https://e14n.com/evan"],
  "actor": ["https://dustycloud.org/chris/"],
  "object": "https://rhiaro.co.uk/2016/05/minimal-activitypub"
}

Validating FastAPI Request Bodies

FastAPI uses Pydantic models to validate request bodies. After importing ActivityPubdantic models directly, developers can automatically validate requests and then use the get_class_from_model() function to smoothly interact with ActivityPub JSON.

When the same Like activity is sent in the POST request to /outbox, the request body is validated by FastAPI and loaded into an ActivityPubdantic class to produce clean JSON.

import activitypubdantic as ap
from activitypubdantic.models import *
from fastapi import FastAPI, Response

app = FastAPI()

# Route for an ActivityPub outbox
@app.post("/outbox", status_code=201)
async def outbox(activity: ActivityModel, response: Response):

    # Initialize the class and perform relevant data manipulations
    activity_class = ap.get_class_from_model(activity)
    activity_class.make_public()

    # Save the JSON in the outbox in the database
    print(activity_class.json())

    # Use the type to set the header
    response.headers["Location"] = "https://example.com/{0}/{1}".format(
        activity_class.type.lower(),
        1,  # ID should come from the database
    )

    # Return with header and status code
    return

Methods – like make_public() – perform common operations on the data. In this case, make_public() removes the bto and bcc attributes from the class instance, if they exist. Additionally, the type attribute specifies a location in the response header, per the ActivityPub documentation for client-to-server interactions.

Contributing

ActivityPubdantic is still a work in progress. If you find it valuable for your project but notice bugs, need changes, or require additional features or support for other ActivityPub platforms, open an issue or fork to start a PR.

The developer_requirements.txt file includes all of the packages your virtual environment needs, including pdoc3 for generating new documentation, black for formatting, and pytest for unit tests.

Keep in mind, all PRs require a successful run of the GitHub Workflow for testing, so if you significantly change ActivityPubdantic's structure, be sure to add, alter, or remove relevant tests.

Thank you for your interest!