{"categories":[{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/22"},{"label":"Distributed Computing","url":"https://skillfed.io/packages/category/system-distributed-computing/3"}],"enrichment":{"capability":"Spark is an async-first actor framework for Python that lets you build concurrent and distributed systems by creating actors, sending messages with `tell()` (fire-and-forget) or `ask()` (request-reply), and managing them through a `Syndicate` instance.","skillfed_tags":["actor-model","async-concurrency","message-passing"],"use_cases":["Build concurrent services where independent tasks communicate via message passing instead of shared state.","Create distributed systems with TCP or WebSocket routes connecting actor systems across network boundaries.","Implement workflow pipelines using the `spark.workflow` layer to route messages through a sequence of processing nodes.","Develop fault-tolerant systems with actor supervision, monitoring, and restart policies.","Build NAT-traversal applications using the WebSocket relay for outbound-only connectivity."],"what_it_does":"Spark is an async actor framework that abstracts concurrent work into independent actors that communicate by message passing. You define actors by subclassing `Actor` and implementing `process()`, then create and manage them through a `Syndicate` instance. The core API is minimal: `tell()` for asynchronous fire-and-forget messages and `ask()` for request-reply with timeout. Actors can be organized hierarchically with parent-child relationships, supervision policies (restart, resume, escalate), and monitoring.\n\nBeyond local concurrency, Spark offers opt-in distributed features: TCP routes with HMAC handshake, WebSocket routes for NAT traversal, authenticated federation for remote actor placement, and durable actors backed by SQLiteJournal. A separate `spark.workflow` package provides a higher-level abstraction for routing messages through a directed graph of processing nodes. The framework is in alpha (Development Status 3) and requires Python 3.13.","worth_installing":"Yes, if you are building a new concurrent or distributed system and are comfortable with alpha-stage software. The core API is clean, dependencies are minimal, and there are no known vulnerabilities. The project is actively maintained. Caution: verify that the supervision model and persistence layer meet your production requirements, and note that Python 3.13 is mandatory."},"id":"spark","links":{"html":"https://skillfed.io/packages/spark","md":"https://skillfed.io/packages/spark.md","pypi":"https://pypi.org/project/spark/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-16","license_spdx":null,"license_treatment":"permissive","name":"Spark","python_support":"supports_current","summary":"An easy to use actor model framework in Python"},"popularity":{"monthly_downloads":80523,"position":14288,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.1"}