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esigning an API is neither easy nor cheap. Trying to create an API is definitely more work than releasing a product without any API at all. Still, in the context of cluelessness, the main message of this book is that with a proper API, you can design better systems while minimizing your own understanding of them. Properly designing and using the APIs of individual components of the system can improve the system engineering methodologies used to design them. Improving your system engineering skills is a way to maximize the benefits of cluelessness.

TIMSK1 = ( _BV(ICIE1) | _BV(TOIE1) ); } Because the weather station receiver is likely to be left running indefinitely, we need to add a little workaround for a design problem in the core Arduino system In most projects it s enough to use the millis() function to return the number of milliseconds since the Arduino started up, but unfortunately the value is stored internally in an unsigned long integer meaning that it can only store a maximum value of up to 2^32 In milliseconds that works out to about 49 days and 17 hours, after which any timing in the program can go drastically wrong To get around this problem we define an interrupt service routine (ISR) to be executed whenever the ATMega s internal Timer1 overflows Timer1 increments on every CPU cycle so it overflows very fast about every 262144ms for a CPU running at 16Mhz.

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The cluelessness model is based on using big building blocks collected from software projects all over the world. By reusing as much as possible, and not writing everything entirely inhouse, product teams can concentrate on the most important differentiator: the actual logic of their application. They no longer need to spend time creating and writing the infrastructure; instead, they can reuse frameworks and other useful libraries produced by others. Nobody writes an SQL database server in-house anymore. People reuse database servers provided by established commercial vendors or emerging open source alternatives. Bothering with an implementation of an SQL database server for private use would be seen as an ineffective waste of resources. The same is happening in many other areas of software technology. Web and application servers, languages and their libraries, integrated development environments (IDEs), and rich client application frameworks are all becoming well-established building blocks. Just like prepackaged dinners or prefabricated blocks of apartments, they can just be taken off the shelf, assembled, and then polished as needed. This approach greatly shortens the development time necessary for producing a software system. When assembling the whole application, you need to glue together individual building blocks. These blocks need to talk to each other somehow. Usually they do so by means of well-defined APIs. Each component s API is an initial step toward increasing your cluelessness. It isn t necessary to understand and know all the internals of each component; it s usually enough to read the component s documentation and use its API to include it successfully in your own application. The API minimizes the need to understand every detail of a component serving as a building block.

The last line shown previously set the Timer Overflow Interrupt Enable, which then causes this next function to be automatically executed every time an overflow occurs Then on every call to this ISR we increment an unsigned long integer, giving us a counter that steps up in increments of 262144ms It can still only count to 2^32, like millis(), but because it s updating only 1/262 as fast it will last 262 times as long (ie, about 35 years) before it will overflow Even when it does overflow, though, it won t be a problem for this particular program because the value is only ever used to calculate a delta against the previous timestamp As long as the delta calculation is performed using the same 32-bit unsigned data types, the delta will still read correctly even when an overflow has happened between one timestamp and the next.

It s also worth noting that many of Django s own APIs work the same way, or in extremely similar ways, with many different types of models. For example, a Django QuerySet has the same methods all(), filter(), get(), and so on regardless of which model it ends up querying against. This means that you can often write code that accepts a QuerySet as an argument and simply applies standard methods to it.

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