I was having really atrocious internet speeds in my bedroom. My download speed was roughly 5 mbps while my upload speed was sometimes as bad as 0.5 mbps. I was manually testing this using a tool I found online but it was taking me a few minutes just to collect a single row of data. It was less than ideal and I was wasting a plethora of my time. I knew I needed to collect a lot of data to empirically prove that the new router I purchased was actually worse than my current despite the specifications stating that it would preform better.
To automate this task I knew I would need an API to test my internet speed. I quickly did some research and found speedtest-cli and pyspeedtest. Both seemed like reasonable options but I ultimately chose pyspeedtest because of its simple API and zero configuration required.
After I had chosen the API it was time to start implementing. Initially, I wrote the output to a csv file and copied it over to a Google doc. That got old fast so I looked for a Python API client for Google docs. Once the Google docs API client was set up I began writing my data directly to Google docs removing all manually aspects of this task aside from running it.
While the scripts ran on various devices I would go run errands or do some chores. I did make a substantial error, if any one of the SpeedTest#ping(), SpeedTest#download() or SpeedTest#upload() were to fail to connect to the test server the whole script would crash. That was a problem because if the script crashes it won't write any of its data to Google docs.
This error became quite frustrating while testing poor connections because I would essentially lose all data collect up until that point. Since I only write the data once, after I have collected it all from the different tests the only solution was to try-catch the individual test. Now, the script would not crash on an individual test failure and it would continue trying to collect data.
I collected 313 rows of data. Manually collecting data took me approximately 3 minutes per row. To collect 313 rows of data it would have taken me roughly 16 hours. I spent 4 hours writing the script (2 of which was wrestling with and learning the Google Docs API), I spent 2 hours doing analysis of the data and I probably spent another hour or so administering the scripts on various devices while doing other things. Meaning, in total, I spent 7 hours on this task and saved myself 9 hours of time if I were to collect as much data.
The data collected result in me empirically proving that my newly purchased router was actually slower than my current router. I quickly went to the store and bought a higher quality router. I am happy to inform you that my internet speeds are roughly 80 mbps and 20 mbps for download and upload respectively. Not too bad for being behind 4 walls and as far away from the router as you possibly can be in my house.