Google Cloud Platform (GCP) can run Python scripts. In general, GCP provides the same functionality and performance as Google Cloud Platform Standard Edition (GCP Standard Edition), with additional features for larger organizations.
You can find more information on the GCP Python runtime on the GCP Python runtime documentation page.
In this article, we’ll show you how to set up and run a simple Python script on GCP. We’ll also discuss some common issues and solutions.
Setup
To get started, you’ll first need a Google Cloud Platform account and set up your GCP account. You can sign up for a free account at g.
co/2FzNcxH.
Once you have your GCP account set up, you can create a project. A project is a logical grouping of resources that you can use to manage your code and data.
To create a project, open the GCP Console and click the Create Project button.
Next, name your project and select a region. You can also choose a platform: Google Cloud Platform (GCP) or Google Cloud Platform Standard Edition (GCP Standard Edition).
To get started with your project, you’ll need the Google Cloud Platform SDK for Python. You can install the SDK by clicking the Install button in the GCP Console.
Once you have the SDK installed, you can initialize it by running the gcloud init command. This command initializes your project and sets up your GCP account.
Run a Python Script on GCP
Now that you have your project set up, you can start running your Python script. To run your script, you’ll first need to create a file called myscript.
py in your project’s root directory.
In myscript.py, you’ll need to import the Google Cloud Platform libraries. You can do this by adding the following import statement to the top of the file:
from google.cloud.
python.gcp import *.
Next, you’ll need to create a Cloud Storage bucket to store your script files. To do this, you can use the following code block to create a bucket called myscriptbucket:
bucket = gcp.storage.bucket( ‘ myscriptbucket ‘ )
You can then use the Cloud Storage library to save your script files to the myscriptbucket bucket. To do this, you can use the following code block to save the file myscript.py to the myscriptbucket bucket:
bucket.put( ‘ myscript.py ‘ , ‘ /myscriptbucket ‘ )
Note: The path to the file must include the bucket name, the file extension (.py), and the file path.
You can also use the Cloud Storage library to get the file size and duration of a file. To do this, you can use the following code block to get the file size of myscript.py in bytes and the file duration in seconds:
size = bucket.size() duration = bucket.size_info()
Finally, you can run your script by using the Python run command. To do this, you can use the following code block to run myscript.py on port 8000 in the myscriptbucket bucket:
run( ‘ myscript.py ‘ , 8000 , ‘ myscriptbucket ‘ )
You can also use the Python run command to run your script in a sandbox. To do this, you can use the –sandbox flag.
run( ‘ myscript.py ‘ , 8000 , ‘ myscriptbucket ‘ , ‘ –sandbox ‘ )
You can also use the Python run command to run your script on a remote machine. To do this, you can use the –remote flag.py ‘ , 8000 , ‘ myscriptbucket ‘ , ‘ –remote ‘ )
You can also use the Python run command to run your script in a dev environment. To do this, you can use the –dev flag.py ‘ , 8000 , ‘ myscriptbucket ‘ , ‘ –dev ‘ )
Finally, you can use the Python run command to run your script in a prod environment. To do this, you can use the –prod flag.py ‘ , 8000 , ‘ myscriptbucket ‘ , ‘ –prod ‘ )
Conclusion
In this article, we showed you how to set up and run a simple Python script on GCP. We also discussed some common issues and solutions.
