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You can check if os.environ['HTTP_HOST'].endswith('.appspot.com') -- if so, then you're serving from something.appspot.com and can send a redirect, or otherwise alter your behavior as desired.

You could deploy this check-and-redirect-if-needed (or other behavior alteration of your choice) in any of various ways (decorators, WSGI middleware, inheritance from an intermediate base class of yours that subclasses webapp.RequestHandler [[or whatever other base handler class you're currently using]] and method names different than get and post in your application-level handler classes, and others yet) but I think that the key idea here is that os.environ is set by the app engine framework according to CGI standards and so you can rely on those standards (similarly WSGI builds its own environment based on the values it picks up from os.environ).

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If the date stored in your database by using NOW() is incorrect, then you need to change your MySQL server settings to the correct timezone. If it's only incorrect once you print it, you need to modify your php script to use the correct timezone.

Edit:

Refer to W3schools' convenient php date overview for information on how to format the date using date().

Edit 2:

Either you get GoDaddy to change the setting (doubtful), or you add 3 hours when you insert into the table. Refer to the MySQL date add function to modify your date when you set it in the table. Something like date_add(now(), interval 3 hour) should work.

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Basically, Python lists are very flexible and can hold completely heterogeneous, arbitrary data, and they can be appended to very efficiently, in amortized constant time. If you need to shrink and grow your list time-efficiently and without hassle, they are the way to go. But they use a lot more space than C arrays, in part because each item in the list requires the construction of an individual Python object, even for data that could be represented with simple C types (e.g. float or uint64_t).

The array.array type, on the other hand, is just a thin wrapper on C arrays. It can hold only homogeneous data (that is to say, all of the same type) and so it uses only sizeof(one object) * length bytes of memory. Mostly, you should use it when you need to expose a C array to an extension or a system call (for example, ioctl or fctnl).

array.array is also a reasonable way to represent a mutable string in Python 2.x (array('B', bytes)). However, Python 2.6+ and 3.x offer a mutable byte string as bytearray.

However, if you want to do math on a homogeneous array of numeric data, then you're much better off using NumPy, which can automatically vectorize operations on complex multi-dimensional arrays.

To make a long story short: array.array is useful when you need a homogeneous C array of data for reasons other than doing math.

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