Code Repository for Interacting with Workflows (Python)

This repository provides code used for exercises and demonstrations included in the Python version of the Interacting with Workflows training course.

It's important to remember that the example code used in this course was designed to support learning a specific aspect of Temporal, not to serve as a ready-to-use template for implementing a production system.

For the exercises, make sure to run temporal server start-dev --ui-port 8080 --db-filename clusterdata.db in one terminal to start the Temporal server. For more details on this command, please refer to the Setting up a Local Development Environment chapter in the course. Note: If you're using the Gitpod environment to run this exercise, you can skip this step.

Hands-On Exercises

Directory Name	Exercise
exercises/sending-signals-external	Exercise 1
exercises/sending-signals-client	Exercise 2
exercises/querying-workflows	Exercise 3
exercises/async-activity-completion	Exercise 4

Samples

Directory Name	Description
samples/custom-search-attributes	Shows a sample of how to use Custom Search Attributes to find queries where the order for pizzas has failed

Reference

The following links provide additional information that you may find helpful as you work through this course.

• General Temporal Documentation
• Temporal Python SDK Documentation
• Python Language Documentation
• Python Packaging and Virtual Environment Documentation
• GitPod Documentation: Troubleshooting

Set Up Your Python Virtual Environment

All Python libraries for this course should be installed in a virtual environment. If you are running these exercises in the course's GitPod environment, there is a virtual environment already setup for you and you can skip this section. If you are running these exercises locally, be sure you are using Python 3.7+.

1. Open a terminal window in the environment and change directories to the root directory of the edu-interacting-with-workflows-python-code repository
2. Run the following command to create a virtual environment

$ python3 -m venv env

3. Activate the virtual environment

Linux/Mac:

$ source env/bin/activate

Windows:

$ env\Scripts\activate

Once the environment is active you should see (env) prepended to your prompt similar to below

(env) $

4. Install the necessary packages into the virtual environment

python -m pip install -r requirements.txt

5. For every new terminal you open, you will need to activate the environment using the following command

Linux/Mac:

$ source env/bin/activate

Windows:

$ env\Scripts\activate

However, the packages are already installed, so there is no need to run pip again.

Exercise Environment for this Course

You can launch an exercise environment for this course in GitPod by clicking the button below:

Alternatively, you can perform these exercises directly on your computer. Refer to the instructions about setting up a local development environment, which you'll find in the "About this Course" chapter.