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edu-102-python-code's Introduction

Code Repository for Temporal 102 (Python)

This repository provides code used for exercises and demonstrations included in the Python version of the Temporal 102 training course.

Hands-On Exercises

Directory Name Exercise
exercises/durable-execution Exercise 1
exercises/testing-code Exercise 2
exercises/debug-activity Exercise 3

Examples for Self-Study

Directory Name Description
samples/age-estimation Calls a remote API to estimate the age of a person given their name
samples/using-dataclasses-as-input-and-output Demonstrate how data classes are passed in as input and output

Reference

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

Setup 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. (Be certain that you are running Python 3.7+. If you system has)

  1. Open a terminal window in the environment and change directories to the root directory of the edu-102-python-code repository
  2. Run the following command to create a virtual environment
$ python3 -m venv env
  1. 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) $
  1. Install the necessary packages into the virtual environment
python -m pip install -r requirements.txt
  1. 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:

Open in Gitpod

Alternatively, you can follow these instructions to set up your own Temporal Cluster with Docker Compose, which you can use as an exercise environment.

edu-102-python-code's People

Contributors

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