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Auto Playlist Poetry

This little (web)app automatically generates Spotify playlists based on a search query entered by the user. Auto Playlist Poetry is a proof-of-concept that's inspired by Playlist Poetry, which in turn was based on this Tumbler blog. The idea is that the user can provide a message and the application will use the Spotify Metadata API to find songs whose titles together make up the provided message.

Aside from the Flask app, there's also a simple commandline utility that does the same thing.

You can find AutoPlaylistPoetry running online here.


A few caveats (ok, excuses really :) ) before trying out this app, and looking through the code:

  • The way playlists get generated is somewhat involved I haven't smoothed out the algorithm completely yet. This means that it will sometimes get caught in some kind of loop, making the web app hang. Shouldn't occur too often though. Solutions and better ideas are welcome!
  • The largest problem currently, is that it can handle single sentences, and maybe a couple of small sentences together, but nothing more than that. I will hang. This is probably due to the algorithm and the way I use threading (see code), but I've not found out yet how to fix it.
  • No Test-coverage whatsoever. You read that right. I know, it's a shame. I would have loved to provide tests for everything, but so far the time spent on this project was limited, and I consider this a proof-of-concept. Do know, that I am well aware of best practices in Software Engineering and that I normally go out of my way to provide decent test-coverage for the code I write. Tests are at the top of my TODO list for this project.
  • External dependencies may make these applications fail sometimes. The Spotify Metadata API was somewhat fickle, and would sometimes return either a undocumented HTTP 502 or 504 error. I haven't seen any odd behaviour since moving to the new Web API though.
  • Python is relatively new to me: In my current job I mainly develop in Scala & Java. I've done some Python programming as a hobby for some time now, and I really love the language! But I'm sure many of my solutions are "un-pythonic". I especially was unsure about how to organize my code, coming from an environment where everything is a class, and almost every class has it's own file. So I don't really know which code to put in what module/package/class/etc. Any ideas, contributions, PRs are welcome!

Installation/usage instructions

As said, there are two versions of the app: a command line app and a web app. Both (can) use Redis for caching the API results for later reuse. In the command line app, using Redis is optional, the web app requires it. You can install Redis using your favorite package manager, such as homebrew on OS X. Aside from redis, two other external Python libraries are used: requests is used by both implementations for querying the Spotify Metadata API and Flask is used as a web framework in the web app.

First clone the repo:

git clone

To install the requirements, you can (assuming you have pip installed) do the following in your terminal:

pip install -r requirements.txt

If you only want to try out the command line app locally (which is easier), you could choose to only install requests and optionally redis.

The command line app

The command line app has two different modes of operation: one-off or interactive. The latter can be invoked by passing -i or --interactive as an argument on the command line. Review the help by running:

./ --help

To run it for one message:

./ -m "if i can't let it go out of my mind"

The app tries to be a good unix-citizen and as such only gives back the endresult, without outputting any other messages during it's runtime. It also gives back 0 on success and non-0 on failure. Should you need more verbosity, you can pass -v. Without it, you only get the URIs for the playlist entries (or optionally the URLs)

The interactive mode let's you type in messages on a prompt, and returns the result. It's straigtforward enough. In iteractive mode, the app, by default, uses an in-memory caching mechanism for storing API results for later reuse. Both interactive and one-off mode can also use Redis by providing the -r switch, with optionally a hostname, port and password. It requires Redis to be running of course.

The web app

To run the web app:


The web application has a very simple interface which needs no further explanation. The application was built using Flask and for the interface I used Twitter Bootstrap (I know! just don't tell any designers…) The app uses Redis for caching API results for later reuse.

The web app also provides a very simple REST API. The endpoint resides at /api/playlist and requires a message to be passed in the query string. It gives back the result in JSON or returns an error in case something went wrong. It also tells you if the result is a complete playlist covering all the words, or if it's a partial result.

Future improvements

Some future improvements could include:

  • (unit)tests
  • Dealing with skipping words to improve results
  • Guarantee a maximum running time by setting time-outs for example. Strive for best-effort. Running time should improve however, when caching is used and the app is used a lot, filling said cache.


...are very welcome!


Generate Spotify playlists from a piece of text



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