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Troubleshooting
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Given the flexibility of the inspyred library, along with the inherent stochasticity of the algorithms, it can be difficult to track down errors that will inevitably arise. This chapter provides some suggestions that may make the process easier. 

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Always Store the Seed
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Every inspyred algorithm requires that a pseudo-random number generator (PRNG) object be passed to it. This allows users to make use of different PRNGs if more sophisticated random number generation is desired (as long as it implements the relevant methods of Python's ``Random`` class). This also means that the PRNG must be seeded prior to its passing to an inspyred algorithm. This seed should always be printed (preferably to a file) in case the exact run of the algorithm needs to be duplicated. If an error occurs in a given run, it can be restarted by providing the same seed. The following code provides an example::

   import random
   import time
   my_seed = int(time.time())
   seedfile = open('randomseed.txt', 'w')
   seedfile.write('{0}'.format(my_seed))
   seedfile.close()
   prng = random.Random()
   prng.seed(my_seed)

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Use and Consult the Logs
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All inspyred algorithms provide detailed debugging data using Python's core ``logging`` module. This can be enabled by adding the following code to the ``main`` or calling scope::

   import logging
   logger = logging.getLogger('inspyred.ec')
   logger.setLevel(logging.DEBUG)
   file_handler = logging.FileHandler('inspyred.log', mode='w')
   file_handler.setLevel(logging.DEBUG)
   formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
   file_handler.setFormatter(formatter)
   logger.addHandler(file_handler)

Consulting the log file will often reveal which component is misbehaving or behaving unexpectedly.

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Choose Operators that Work Together
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The inspyred library gives users freedom to combine operators in almost any way they choose. However, this freedom means that the library will be unable to alert the user when a particular combination of operators produces a nonsensical algorithm. Remember that the operators must work together. For example, tournament selection may be employed to select 20 individuals from a population of 100. Then Gaussian mutation may be used to create 20 offspring. Finally, generational replacement may create the next generation from those offspring. The library will allow this, even though it means that, for at least the first generation, the population size is not constant. (It drops from 100 to 20.) The reason such a thing is allowed is because there may be a need for an algorithm that requires a non-constant population size. The inspyred library does not restrict any such algorithm. It is up to the user to ensure that all components work together to achieve the desired ends. (As stated previously, consulting the log file can help determine whether operators are combined correctly.)