Python for Entrepreneurs Transcripts
Chapter: Appendix: Python language concepts
Lecture: Concept: Named tuples
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In the previous section we discussed tuples, and how they are useful.
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Sometimes these anonymous tuples that we discussed are exactly what you need,
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but oftentimes, it's very unclear what values are stored in them,
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especially as you evolve the software over time.
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On the second line here, we have "m", a measurement we are defining
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this time it's something called a named tuple
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and just looking at that definition there on what we are instantiating
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the measurement, it's not entirely clear the first value is the temperature,
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the second value is the latitude, this third value is a longitude, and so on.
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And we can't access it using code that would treat it like a plain tuple,
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here we say the temperature is "m" of zero
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which is not clear at all unless you deeply understand this
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and you don't change this code, but because we define this as a named tuple,
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here at the top we define the type by saying
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measurement is a collections.namedtuple,
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and it's going to be called a measurement,
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for error purposes and printing purposes and so on,
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and then you define a string which contains all the names for the values.
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So over here you are going to say this type of tuple temperature's first, then latitude,
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then longitude, then quality, and what that lets us do is access those values by name.
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So instead of saying "m" of zero temperature,
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we say m.temp is the temperature, and the quality is m.quality.
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Named tuples make it much easier to consume these results
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if you are going to start processing them
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and sharing them across methods and things like that.
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Additionally, when you print out a named tuple it actually prints a friendlier version
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here at the bottom you see measurement of temperature, latitude, longitude, and quality.
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So most of the time if you are thinking about creating a tuple,
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chances are you should make a named tuple.
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There is a very small performance overhead but it's generally worth it.
