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Even if some of this work is done inefficiently today in any particular implementation, there is a limit to how much it can be improved and sped up.This leads to a straightforward conclusion: to really get faster, a Python implementation must do less work.

Just, no one knows it because it isn't in the job title.

If the company is one that bases annual compensation improvements on the previous year's performance, this judgment happens every year and compounds. Suddenly, five engineers are now hammering to get raises because they had Only one person will be banging on doors, Engineer number 5.

The kernel provides the appropriate helpers for this task.

After this change, we have two new files in min=72 max=33364 count=100000 95th=154 90th=142 50th=112 mad=6 value │ ┊ count 72 │ 51 77 │▒ 3548 82 │▒▒░░ 4773 87 │▒▒░░░░░ 5918 92 │░░░░░░░ 1207 97 │░░░░░░░ 437 102 │▒▒▒▒▒▒░░░░░░░░ 12164 107 │▒▒▒▒▒▒▒░░░░░░░░░░░░░░ 15508 112 │▒▒▒▒▒▒▒▒▒▒▒░░░░░░░░░░░░░░░░░░░░░░ 23014 117 │▒▒▒░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 6297 122 │░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 905 127 │▒░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 3845 132 │▒▒▒░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 6687 137 │▒▒░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 4884 142 │▒▒░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 4133 147 │░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 1015 152 │░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 1123 If the benchmark is running using the same input parameters over and over, the input data may fit entirely in the L1 cache. Therefore, it is important to iterate over a large dataset.

Beware, random posts found on the web (including this one) may be outdated.

The IPv4 address is stored as a 32-bit integer but displayed and parsed using the dotted quad notation.

Implementation tweaks can speed them up to some degree, but to get significant speed improvements they must do less work.

In Yesterday Apple issued an apology for the intentional slowing of i Phones because of aging in the i Phone battery. When you put Eclipse/Vim/Visual Studio behind you, then you're a manager.

A regular dataset may still affect positively the benchmark despite its size.

While the whole dataset will not fit into L1/L2 cache, the previous run may have loaded most of the data needed for the current run.

Python's dynamic typing and the power it gives you over objects means that apparently simple actions can unpredictably do complex things.

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