Stay current on Python, a general-purpose, high-level, and interpreted programming language.
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Learn how to use Google Cloud Platform product libraries and frameworks to build, deploy, and monitor Python apps at scale. Use Google's APIs with Python to get actionable insights from your data.
Learn how to create Python applications that dynamically scale capacity up or down according to traffic, perform data analysis, build machine learning models using powerful APIs, and more.
Integrate with various Google Cloud Platform products from the comfort of Python.
Prepare your local machine for Python development, including developing Python apps that run on Google Cloud Platform.
Playlists and codelabs
Cloud Run is a managed compute platform that enables you to run stateless containers that are invocable with HTTP requests. Cloud Run is serverless: it abstracts away all infrastructure management, so you can focus on what matters most — building great applications. In this codelab, you create a Python application and deploy it to Cloud Run.
Cloud Functions is an event-driven serverless compute platform. Cloud Functions allows you to write your code without worrying about provisioning resources or scaling to handle changing requirements. In this codelab, you create a Cloud Function in Python that is invoked with HTTP.
The Google Cloud Vision API allows you to easily integrate vision detection features into applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content. In this codelab, you focus on using the Vision API with Python, and learn how to perform text detection, landmark detection, and face detection!
App Engine applications are easy to create, easy to maintain, and easy to scale as your traffic and data storage needs change. With App Engine, there are no servers to maintain. You simply upload your application and it's ready to go. In this codelab, you learn how to deploy a simple Python web app written with the Flask web framework.
This codelab shows you how to create a data preprocessing pipeline using Apache Spark, Cloud Dataproc, BigQuery, Cloud Storage, and Reddit posts data. This codelab uses PySpark, which is the Python API for Apache Spark.
This codelab focuses on using the Cloud Natural Language API with Python. In this codelab, you learn how to perform sentiment analysis, entity analysis, syntax analysis, and content classification.
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