It is possible to use generic Python objects as the dtype for a NumPy array, but if you do this, you’ll get no better performance with NumPy than you would with Python generally.

That was [gnebehay’s] thought when his university studies were too high level, so he decided to write an arithmetic expression parser in Python. It came out in about 100 lines of code.

For us it’s easy to do 8-bit math in our head, but doubling that is another story. The image above is one screenshot from [Joe’s] tutorial.

Many programming languages include libraries to do more complicated math. You can do statistics, numerical analysis or handle big numbers. One topic many programming languages have difficulty with is ...