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If when we run the instrumented program we nd that the arguments are correct but that the return value is in error, we know that we have located the source of the bug and can further investigate the function If looking carefully at the function doesn t suggest where the problem lies, we can simply insert a new print(locals(), "\n") statement right in the middle After running the program again we should now know whether the problem arises in the rst or second half of the function, and can put a print(locals(), "\n") statement in the middle of the relevant half, repeating the process until we nd the statement where the error is caused This will very quickly get us to the point where the problem occurs and in most cases locating the problem is half of the work needed to solve it The alternative to adding print() statements is to use a debugger Python has two standard debuggers One is supplied as a module (pdb), and can be used interactively in the console for example, python3 -m pdb my_programpy (On Windows, of course, we would replace python3 with something like C:\Python31\pythonexe) However, the easiest way to use it is to add import pdb in the program itself, and add the statement pdbset_trace() as the rst statement of the function we want to examine When the program is run, pdb stops it immediately after the pdbset_trace() call, and allows us to step through the program, set breakpoints, and examine variables Here is an example run of a program that has been instrumented by having the import pdb statement added to its imports, and by having pdbset_trace() added as the rst statement inside its calculate_median() function (What we have typed is shown in bold, although where we typed Enter is not indicated).

FIGURE 97 The Orders submodel from the Mountain View Music logical model First, let s look at the entities that can be made into tables as is We have already made tables out of the Products and Employees entities, so those two are all set (with a single exception for tbl_employee, which we look at shortly) Of the remaining entities, Shipments, ShippingMethods, ShippingCarriers, and Order Details can all be made into tables without any major modification other than their names That leaves us with six entities that still need some work: Orders, Customers, and the supertype

Figure 535 Pseudocode for an ineffective approach to parallelizing the population shuffle in the genetic algorithm program GAFORT

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python3 statisticspy sumdat > statisticspy(73)calculate_median() -> numbers = sorted(numbers) (Pdb) s > statisticspy(74)calculate_median() -> middle = len(numbers) // 2 (Pdb) > statisticspy(75)calculate_median() -> median = numbers[middle] (Pdb) > statisticspy(76)calculate_median() -> if len(numbers) % 2 == 0: (Pdb) > statisticspy(78)calculate_median() -> return median (Pdb) p middle, median, numbers (8, 50, [-170, -95, 00, 10, 30, 40, 40, 50, 50, 50, 55, 60, 70, 70, 80, 90, 170]) (Pdb) c

Commands are given to pdb by entering their name and pressing Enter at the (Pdb) prompt If we just press Enter on its own the last command is repeated So here we typed s (which means step, ie, execute the statement shown), and then repeated this (simply by pressing Enter), to step through the statements in the calculate_median() function Once we reached the return statement we printed out the values that interested us using the p (print) command And nally we continued to the end using the c (continue) command This tiny example should give a avor of pdb, but of course the module has a lot more functionality than we have shown here It is much easier to use pdb on an instrumented program as we have done here than on an uninstrumented one But since this requires us to add an import and a call to pdbset_trace(), it would seem that using pdb is just as intrusive as using print() statements, although it does provide useful facilities such as breakpoints The other standard debugger is IDLE, and just like pdb, it supports single stepping, breakpoints, and the examination of variables IDLE s debugger window is shown in Figure 91, and its code editing window with breakpoints and the current line highlighted is shown in Figure 92

One great advantage IDLE has over pdb is that there is no need to instrument our code IDLE is smart enough to debug our code as it stands, so it isn t intrusive at all Unfortunately, at the time of this writing, IDLE is rather weak when it comes to running programs that require command-line arguments The only way to do this appears to be to run IDLE from a console with the required arguments,

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