PyCharm AWS Tutorial: An Interview with Mukul Mantosh
We’ve been talking about PyCharm and popular cloud platforms recently. The AWS Toolkit for IntelliJ is a plugin that works with PyCharm and our other IDEs. How do you use it? How do you use AWS? Mukul Mantosh produced a 10-part video+text+code tutorial Deploying Serverless APIs using AWS Toolkit for our PyCharm Guide. It’s a wonderful resource for those getting started, covering: setup, cloud d
Running Flask with an SSH Remote Python Interpreter
One common cause of bugs in many applications is that development and production environments differ. Although in most cases it’s not possible to provide an exact copy of the production environment for development, pursuing dev-prod parity is a worthwhile cause. Most web applications are deployed to some sort of Linux VM. If you’re using a traditional web-host, this is referred to as VPS hosting.
Creating a Python Development Environment on Amazon EC2
In the last two blog posts of this series we discussed how to set up a local VM-based development environment for a cloud application, and then built a Flask-RESTful app within this environment. Today, we’ll take our app to AWS, and we’ll set up a remote development environment. The environment we’ll describe here is configured for development, not production. If you’re interested in seeing how to
Analyzing Data in Amazon Redshift with Pandas
Redshift is Amazon Web Services’ data warehousing solution. They’ve extended PostgreSQL to better suit large datasets used for analysis. When you hear about this kind of technology as a Python developer, it just makes sense to then unleash Pandas on it. So let’s have a look to see how we can analyze data in Redshift using a Pandas script! Setting up Redshift If you haven’t used Redshift before, yo