>Unless you've actually profiled the thing and shown where the time is used, all your assertions are nonsense.

It's data science that is causing this data driven attitude to invade peoples minds. Do you not realize that logic and assumptions take a big role in drawing conclusions WITHOUT data? In fact if you're a developer you know about a way to DERIVE performance WITHOUT a single data point or benchmark or profile. You know about this method, you just haven't been able to see the connections and your model about how this world works (data driven conclusions only) is highly flawed.

I can look at two algorithms and I can derive with logic alone which one is O(N) and which one is O(N^2). There is ZERO need to run a benchmark. The entire theory of complexity is a mathematical theory used to assist us at arriving AT PERFORMANCE conclusions WITHOUT EVIDENCE/BENCHMARKS.

Another thing you have to realize is the importance of assumptions. Things like 1 + 1 = 2 will remain true always and that a profile or benchmark ran on a specific task is an accurate observation of THAT task. These are both reasonable assumptions to make about the universe. They are also the same assumptions YOU are making everytime you ask for EVIDENCE and benchmarks.

What you aren't seeing is this: The assumptions I AM making ARE EXACTLY THE SAME: reasonable.

>you're asserting something without actual evidence, and the article itself doesn't actually state that either: it contains no breakdown of where the time is spent

Let's take it from the top shall we.

I am making the assumption that tasks done in parallel ARE Faster than tasks done sequentially.

The author specifically stated he made a server that where each request fetches a row from the database. And he is saying that his benchmark consisted of thousands of concurrent requests.

I am also making the assumption that for thousands of requests and thousands of database requests MOST of the time is spent on IO. It's similar to deriving O(N) from a for loop. I observe the type of test the author is running and I make a logical conclusion on WHAT SHOULD be happening. Now you may ask why is IO specifically taking up most of the time of a single request a reasonable assumption? Because all of web development is predicated on this assumption. It's the entire reason why we use inefficient languages like python, node or Java to run our web apps instead of C++, because the database is the bottleneck. It doesn't matter if you use python or ruby or C++, the server will always be waiting on the db. It's also a reasonable assumption given my experience working with python and node and databases. Databases are the bottleneck.

Given this highly reasonable assumption, and in the same vein as using complexity theory to derive performance speed, it is highly reasonable for me to say that the problem IS PYTHON SPECIFIC. No evidence NEEDED. 1 + 1 = 2. I don't need to put that into my calculator 100 times to get 100 data points for some type of data driven conclusion. It's assumed and it's a highly reasonable assumption. So reasonable that only an idiot would try to verify 1 + 1 = 2 using statistics and experiments.

Look you want data and no assumptions? First you need to get rid of the assumption that a profiler and benchmark is accurate and truthful. Profile the profiler itself. But then your making another assumption: The profiler that profiled the profiler is accurate. So you need to get me data on that as well. You see where this is going?

There is ZERO way to make any conclusion about anything without making an assumption. And Even with an assumption, the scientific method HAS NO way of proving anything to be true. Science functions on the assumption that probability theory is an accurate description of events that happen in the real world AND even under this assumption there is no way to sample all possible EVENTS for a given experiment so we can only verify causality and correlations to a certain degree.

The truth is blurry and humans navigate through the world using assumptions, logic and data. To intelligently navigate the world you need to know when to make assumptions and when to use logic and when data driven tests are most appropriate. Don't be an idiot and think that everything on the face of the earth needs to be verified with statistics, data and A/B tests. That type of thinking is pure garbage and it is the same misguided logic that is driving your argument with me.