Perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away.- Antoine de Saint-Exupéry
Light. Falcon follows the minimalist philosophy. Only the essentials are included, with six and mimeparse the only dependencies beyond the standard library. We work to keep the code lean, making Falcon easier to test, optimize, and deploy.
Fast. Cloud APIs need to turn around requests quickly, and make efficient use of hardware. Falcon processes requests several times faster than other popular web frameworks.
Explicit. Falcon eschews magic. The last thing you want is your framework doing sneaky things behind your back. It's obvious which inputs lead to which outputs, and where variables originate. All this makes it easier to extend the framework, reason about the code, and debug edge cases in large-scale deployments of your application.
Performance. Unlike other Python web frameworks, Falcon won't bottleneck your API's performance under highly concurrent workloads. Many frameworks max out at serving simple "hello world" requests at a few thousand req/sec, while Falcon can easily serve many more on the same hardware. Considering a move to another programming language? Benchmark with Falcon + PyPy first.
Freedom. Falcon isn't very opinionated. In other words, the framework leaves a lot of decisions and implementation details to you, the API developer. This gives you a lot of freedom to customize and tune your implementation in order to create a solution that stands out from the crowd. Due to Falcon's minimalist design, Python community members are free to independently innovate on Falcon add-ons and complimentary packages. You can take advantage of these projects, as well as extend the framework yourself in a variety of ways to create a best-fit solution for your web application.
Reliability. Falcon doesn't include a lot of cruft that is simply unnecessary when building web services. Less code and fewer dependencies means a smaller attack surface, lower memory usage, and fewer places for bugs to hide. Our build fails at anything less than 100% code coverage. We use Travis and Codecov to keep ourselves honest.
Scenario. The benchmark acts as a WSGI server and performs a GET request directly on each framework's app. Each app parses a route template with a single embedded parameter, reads a query parameter and a header from the request data, sets an x-header on the response, and finally returns a 10 KiB plain-text body, randomly generated.
Method. 20,000 iterations were executed per trial, and the best time was recorded for each framework over 20 trials. The order in which the frameworks were tested was randomized for each trial. Also, garbage collection was enabled as it would be in a production environment, and a full collection was forcefully triggered before each trial. Finally, results were calculated using the Decimal class, and rounded to the nearest whole number.
Platform. Benchmarks were executed on a DigitalOcean 1GB VM, running Ubuntu 16.04.2 with all system packages updated to their latest versions as of May 2017. The frameworks were tested on several different versions of Python. Note that in these tests the Falcon modules were not cythonized; generally speaking, the reader may expect a ~10% boost in performance when Falcon is installed with Cython.
Extended Test. Falcon was also benchmarked under CPython 2.7.13 with a more realistic scenario, in which the routing table had multiple entries, the query string contained percent-encoded characters, and several complex response headers were set in the response. Note that even when Falcon is doing more work, it still is able to outperform other frameworks, such as Bottle, which are only doing the bare minimum to construct a response.