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Python

Local Speed, Smooth Deploys: Heroku Adds Support for uv

Ah, another day, another deep dive into the ever-evolving world of Python development! Today, let’s talk about something near and dear to every Pythonista’s heart – managing those crucial external packages. For years, pip has been our trusty companion, the workhorse that gets the job done. But the landscape is shifting, and a new contender has entered the arena, promising speed, efficiency, and a fresh approach: uv.

As a Python developer constantly striving for …

Introducing Heroku-Streamlit: Seamless Data Visualization

We’re excited to announce the release of Heroku-Streamlit, a template that makes deploying interactive data visualization applications on Heroku simpler than ever before. Streamlit is an open-source app framework built for machine learning and data science projects. This Streamlit App brings together Heroku’s scalable cloud platform and Streamlit’s intuitive Python-based data application framework. Whether you’re a data scientist, educator, or developer, you can now spin up a cloud-based Streamlit environment in minutes.

What is Heroku-Streamlit?

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Jupyter Notebooks on Heroku with Persistent Storage

We’re excited to introduce Heroku-Jupyter, an open-source, production-ready solution for running Jupyter Notebooks on Heroku with persistent storage, seamless deployment, and built-in security. Whether you’re a data scientist, educator, or developer, you can now spin up a cloud-based Jupyter environment in minutes.

From Project to Productionized with Python

This blog post is based on From Project to Productionized, a talk given at PyCon 2020 at the height of the COVID-19 pandemic. You can use this post today to learn how to deploy a Python application on Heroku. More specifically, we’ll show you how to deploy Django apps, including setting up your Django configuration, building continuous delivery pipelines, adding middleware, and everything else that goes into deploying Django on Heroku.

If you’d prefer …

Getting to Know Python 3.7: Data Classes, async/await and More!

If you're like me, or like many other Python developers, you've probably lived (and maybe migrated) through a few version releases. Python 3.7(.3), one of the latest releases, includes some impressive new language features that help to keep Python one of the easiest, and most powerful languages out there. If you're already using a Python 3.x version, you should consider upgrading to Python 3.7. Read on to learn more about some of the exciting …

See Python, See Python Go, Go Python Go

Andrey Petrov is the author of urllib3, the creator of Briefmetrics and ssh-chat, and a former Googler and YCombinator alum. He’s here to tell us of a dangerous expedition his requests undertook, which sent them from Python, through the land of C, to a place called Go (and back again).

Today we're going to make a Python library that is actually the Go webserver, for which we can write handlers in Python. It …

Django Channels: How to Build Real-Time Web Apps With Python

Today, we're thrilled to host Jacob Kaplan-Moss. Jacob's a former Herokai and long-time core contributor to Django, and he's here to share an in-depth look at something that he believes will define the future of the framework.

Django Channels allows Python developers to build real-time, asynchronous web apps with Python and JavaScript. It augments Django’s robust response-request architecture with asynchronous protocol handling, including WebSockets support. In this Django Channels tutorial, we’ll show you how …

Django 1.9’s Improvements for Postgres

A big update to the beloved Python web framework known as Django was released recently: Django 1.9. This release contains a long list of improvements for everything from the graphical styling of the admin to the ability to run your test suite in parallel.

Our favorite improvements to the framework were, of course, all about our favorite database: Postgres. Here are some of the highlights from the official release notes (highly recommended reading).

Renamed …

How to Secure the Celery Task Queue with Fernet

Celery is by far the most popular library in Python for distributing asynchronous work using a task queue. If you’re building a Python web app, chances are you already use it to send email, perform API integrations, etc. Many people choose Redis as their message broker of choice because it’s dead simple to set up: provision a Redis add-on, use its environment variable as your BROKER_URL, and you’re done. But the simplicity of Redis comes at a cost. Redis does not currently support SSL, and it doesn’t seem like that’s going to change any time soon. Because Heroku add-ons communicate over the public web, that means the contents of Celery jobs are traveling unencrypted between dynos and Redis.

Waza 2013: How Ecosystems Build Mastery

When we think of the concept of Waza (技) or "art and technique," it's easy to get caught up in the idea of individual mastery. It's true that works of art are often created by those with great skill, but acquiring that skill is neither solitary nor static. Generations of masters contribute to a canon and it is in that spirit that we built the Heroku platform and the Waza event. This year's Waza was …

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