Exploring Durable Execution with Python

What if your Python code could automatically resume after a crash? Learn how durable execution simplifies building resilient, long-running applications.

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The challenge of managing modern distributed systems

Modern distributed systems are powerful but their complexity makes them prone to failures that are difficult to recover from.

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Introducing Temporal for durable execution

Temporal.io is an open-source framework that simplifies complex systems and improves reliability through a concept called durable execution.

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Understanding Temporal workflows and activities

Applications are built using deterministic workflows for business logic and activities for executing individual, potentially fallible tasks.

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How durable execution handles process failures

Durable execution captures the complete state of a function, allowing it to be seamlessly migrated and resumed on another server after a crash.

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Exploring the key capabilities of the Temporal framework

The framework includes built-in features like auto-save, native retries, durable timers, schedules, and signals for human-in-the-loop processes.

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Understanding the architecture of a Temporal application

Developers deploy code to workers that poll the Temporal server for tasks, which in turn captures and stores the complete execution state.

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Implementing a workflow with the Python SDK

A practical example shows how to define a workflow, create activities, implement worker logic, and use a client to send signals.

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Using durable primitives with asyncio in Python

The Python SDK provides durable versions of asyncio primitives like timers, tasks, and cancellations that survive process crashes.

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Advanced SDK features and activity execution styles

The Python SDK is backed by a Rust core and supports multiple activity styles including async, threaded, and multi-process executors for different use cases.