Simon Willison’s Weblog

13 items tagged “heroku”

2020

The value of a product is the number of problems it can solve divided by the amount of complexity the user needs to keep in their head to use it. Consider an iPhone vs a standard TV remote: an iPhone touchscreen can be used for countless different functions, but there’s very little to remember about how it works (tap, drag, swipe, pinch). With a TV remote you have to remember what every button does; the more things you can use the remote for, the more buttons it has. We want to create iPhones, not TV remotes.

Adam Wiggins: Heroku Values # 3rd December 2020, 9:25 pm

Running Datasette on DigitalOcean App Platform (via) I spent some time with DigitalOcean’s new App Platform today, which is a Heroku-style PaaS that starts at $5/month. It looks like it could be a really good fit for Datasette. Disk is ephemeral, but if you’re publishing read-only data that doesn’t matter since you can build the SQLite database as part of the deployment and bundle it up in the Docker/Kubernetes container. # 7th October 2020, 2:52 am

2019

db-to-sqlite 1.0 release. I’ve released version 1.0 of my db-to-sqlite tool, which lets you create a SQLite database copy of any database supported by SQLAlchemy (I’ve tested it against MySQL and PostgreSQL). The tool has a bunch of new features: you can use --redact to redact specific columns, specify --table multiple times to copy a subset of tables, and the --all option now efficiently adds all foreign keys at the end of the import. The project now has unit tests which run against MySQL and PostgreSQL in Travis CI. Also included in the README: a shell one-liner for creating a local SQLite copy of a remote Heroku Postgres database based on extracting the connection string from a Heroku config environment variable. # 1st July 2019, 1:35 am

2018

s3monkey: A Python library that allows you to interact with Amazon S3 Buckets as if they are your local filesystem. (via) A particularly devious hack by Kenneth Reitz—provides a context manager within which various Python filesystem APIs such as open() and os.listdir() are monkeypatched to operate against an S3 bucket instead. Kenneth built it to make it easier to work with files from apps running on Heroku. Under the hood it uses pyfakefs, a filesystem mocking library originally released by Google. # 21st February 2018, 5:54 pm

2017

Try hosting on PyPy by simonw. I had a go at hosting my blog on PyPy. Thanks to the combination of Travis CI, Sentry and Heroku it was pretty easy to give it a go—I had to swap psycopg2 for psycopg2cffi and switch to the currently undocumented pypy3-5.8.0 Heroku runtime (pypy3-5.5.0 is only compatible with Python 3.3, which Django 2.0 does not support). I ran it in production for a few minutes and didn’t get any Sentry errors but did end up using more Heroku dyno memory than I’m comfortable with—see the graph I posted in a comment. I’m going to stick with CPython 3.6 for the moment. Amusingly I did almost all of the work on this on my phone! Travis CI means it’s easy to create and test a branch through GitHub’s web UI, and deploying a tested branch to Heroku is then just a button click. # 5th November 2017, 7:17 pm

Using “import refs” to iteratively import data into Django

I’ve been writing a few scripts to backfill my blog with content I originally posted elsewhere. So far I’ve imported answers I posted on Quora (background), answers I posted on Ask MetaFilter and content I recovered from the Internet Archive.

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Squeezing every drop of performance out of a Django app on Heroku. Ben Firshman describes some lesser known tricks for scaling Django on Heroku—in particular, using gunicorn gevent asynchronous workers and setting up PostgreSQL connection pooling using django-db-geventpool. # 31st October 2017, 2:08 pm

Porting my blog to Python 3

This blog is now running on Python 3! Admittedly this is nearly nine years after the first release of Python 3.0, but it’s the first Python 3 project I’ve deployed myself so I’m pretty excited about it.

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How to set up world-class continuous deployment using free hosted tools

I’m going to describe a way to put together a world-class continuous deployment infrastructure for your side-project without spending any money.

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Running gunicorn behind nginx on Heroku for buffering and logging

Heroku’s default setup for Django uses the gunicorn application server. Each Heroku dyno can only run a limited number of gunicorn workers, which means a limited number of requests can be served in parallel (around 4 per dyno is a good rule of thumb).

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2016

What’s the cheapest or free stack solution to deploy and experiment with a realtime application in 2016?

Heroku have a good free tier, and comprehensive support for deploying both Python and Node.js. If you are mainly interested in realtime I would suggest starting out with Node.js on Heroku. Depending on the complexity of your project you might even be able to use raw Node.js without adding something like Express.

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2013

For a Django application, deployed on Heroku, what are my options for storing user-uploaded media files?

S3 is really a no-brainer for this, it’s extremely inexpensive, very easy to integrate with and unbelievably reliable. It’s so cheap that it will be practically free for testing purposes (expect to spend pennies a month on it).

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2011

The New Heroku (Part 4 of 4): Erosion-resistance & Explicit Contracts. I really like Adam’s description of Software Erosion—I’ve seen that happen to my projects a bunch of times, and it really is an important problem to solve. # 29th June 2011, 5:26 pm