Pydantic v2 type definitions for the Slack APIs:
- Web API (
slack_types.web_api) - Events API (
slack_types.events_api) - Real Time Messaging API (
slack_types.rtm_api) - App backend payloads (
slack_types.app_backend.{dialogs,interactive_components,slash_commands,views}) - Audit Logs API (
slack_types.audit_api.v1) - SCIM API (
slack_types.scim_api.{v1,v2})
PyPI: https://pypi.org/project/slack-types
uv add slack-types
# or
pip install slack-typesfrom typing import Callable
from slack_bolt.async_app import AsyncApp
from slack_sdk.web.async_client import AsyncWebClient
from slack_types.events_api.app_mention_payload import Event as AppMentionEvent
app = AsyncApp()
@app.event("app_mention")
async def handle_mentions(event: dict, client: AsyncWebClient, say: Callable):
mention = AppMentionEvent.model_validate(event)
await client.reactions_add(
channel=mention.channel,
timestamp=mention.ts,
name="eyes",
)
await say("What's up?")
if __name__ == "__main__":
app.start(3000)Web API responses use the same Pydantic interface:
from slack_types.web_api.conversations_history_response import ConversationsHistoryResponse
response = await client.conversations_history(channel="C123")
history = ConversationsHistoryResponse.model_validate(response.data)
for message in history.messages or []:
print(message.ts, message.text)All fields are Optional with defaults of None because Slack does not
guarantee any field on any response. Validate at the boundary; don't rely on
required-ness.
Input samples come from java-slack-sdk (recorded JSON responses). Each sample is converted to a JSON Schema with genson, then handed to datamodel-code-generator to emit a Pydantic v2 module.
Coverage may not be 100% and some properties may be incorrect. File issues at https://github.com/warrenseine/slack-types/issues.
To re-generate:
uv sync --group dev
uv run python scripts/build.py # clones java-slack-sdk/ on first run
uv run pytest # smoke + round-trip testsTo publish:
uv build
uv publishMIT
