All the world is legacy code, and there is always another, lower layer to peel away. These realities cause developers around the world to go on regular pilgrimage, from the terra firma of Python to the coasts of C. From zlib to SQLite to OpenSSL, whether pursuing speed, efficiency, or features, the waters are powerful, and often choppy. The good news is, when you’re writing Python, C interactions can be a day at the beach.
Year after year, Pythonists all over are churning out more code than ever. People are learning, the ecosystem is flourishing, and everything is running smoothly, right up until packaging. Packaging Python is fundamentally un-Pythonic. It can be a tough lesson to learn, but across all environments and applications, there is no one obvious, right way to deploy. Frankly, it’s hard to think of an area where Python’s Zen applies less.
At PayPal, we write and deploy our fair share of Python, and we wanted to devote a couple minutes to our story and give credit where credit is due. For conclusion seekers, without doubt or further ado:Continuum Analytics’ Anaconda Python distribution has made our lives so much easier. For small- and medium-sized teams, no matter the deployment scale, Anaconda has big implications. But let’s talk about how we got here.