In this Temporal with Python course, you will explore the basic building blocks of Temporal: Workflows and Activities. You’ll use these building blocks along with Temporal's Python SDK to develop a small application that communicates with an external service. You'll see how Temporal helps you recover from failures and explore Temporal's execution model and event history. You'll use the Temporal Web UI and Temporal’s command-line tools to explore and interact with your Workflows, and you'll use what you've learned to add new features to your existing Workflow.
Course Objectives:
In this course, you will learn to:
- Configure an environment for developing Temporal Applications
- Use Temporal to describe and implement a business process
- Interpret Temporal's Workflow execution model
- Use Temporal’s tooling to manage the lifecycle of your application
Course content
What is Temporal?
- Introducing Temporal
- What is a Workflow?
- Workflow Examples
- Architectural Overview
- Options for Running a Temporal Cluster
- Integrating Temporal into Other Applications
- Temporal SDKs
- Temporal Command-Line Interface: temporal
Developing a Workflow
- Writing a Workflow Definition
- Input Parameters and Return Values
- Initializing the Worker
Executing a Workflow
- Executing a Workflow from the Command Line
- Executing a Workflow from Application Code
- Lab: Hello Workflow
Viewing Workflow Execution History
- Viewing Workflow History with the Temporal CLI
- Viewing Workflow History from the Web UI
- Lab: Hello Web UI
Modifying an Existing Workflow
- Making Changes to a Workflow
- Restarting the Worker Process
Developing an Activity
- What Are Activities?
- Asynchronous vs. Synchronous Activity Implementations
- Registering Activities
- Executing Activities
- Using Appropriate Timeouts
Handling Activity Failure
- How Temporal Handles Activity Failure
- Activity Retry Policy Example
- Lab: Farewell Workflow
Understanding Workflow Execution
- About This Example
- Code Walkthrough
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Course Prerequisites
- Should have experience writing backend applications that rely on external APIs.
- Developer with minimal Python experience should be able to successfully complete this course.
Who can attend
- Anyone who is trying to build robust applications that require durable execution, such as LLMs, AI applications, Agents, and message queues, among others.
- Anyone looking to stabilize the performance of their distributed systems.
- Software engineers that are looking to build robust distributed systems
Number of Hours: 10hrs
Certification
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- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
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- Preparing for Certification
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